Method for optimizing a resource requirement for a cleaning process, cleaning method, use of a control quantity, cleaning system and motor vehicle

ABSTRACT

A method for optimizing a resource requirement for a cleaning process of a surface of a motor vehicle. Moreover, the method further relates to a cleaning method, a use of a control quantity, a cleaning system, and a motor vehicle.

The present invention relates to a method for optimizing a resourcerequirement for a cleaning process, cleaning method, use of a controlquantity, cleaning system and motor vehicle.

In particular, the present invention relates to a cleaning method, amethod for indirectly deriving a systematic dependence for a systembehaviour of a cleaning system of a motor vehicle, particularlypreferably for a system behaviour of a cleaning process of a surface ofthe motor vehicle, a method for optimizing a resource requirement for acleaning process of a surface of a motor vehicle, a method fordetermining a cleaning strategy for cleaning a surface to be cleaned ofa motor vehicle, a method for indirectly deriving a systematicdependence for a system behaviour of a system component of a cleaningsystem of a motor vehicle, a method for diagnosing a deviation betweenan actual system behaviour and an expected system behaviour of a systemcomponent of a cleaning system of a motor vehicle, a method forselecting a resolution strategy, a use of a selected resolutionstrategy, a method for indirectly deriving a systematic dependence for asystem behaviour of a soiling process of a surface of a motor vehicle, ause of a dependency table and/or a systematic dependence to determine anexpected availability at a distance or an operating time of the motorvehicle yet to be covered, a use of a dependency table and/or asystematic dependence to determine an expected distance or an operatingtime of the motor vehicle yet to be covered when reaching a threshold ofavailability, a use a dependency table and/or a systematic dependencefor optimizing a resource requirement for a cleaning process of asurface of a motor vehicle, a use of a dependency table and/or asystematic dependence to determine a cleaning strategy for cleaning asurface to be cleaned of a motor vehicle, a use a dependency tableand/or a systematic dependence to determine a necessary expected gain inavailability, a use a systematic dependence derived by a method forindirectly deriving a systematic dependence for a resource efficientcleaning of at least one surface of a motor vehicle, a use a controlquantity setpoint derived by a method for optimizing a resourcerequirement for a cleaning process of a surface of a motor vehicle for aresource efficient cleaning of at least one surface of a motor vehicle,a use a cleaning strategy derived by a method for determining a cleaningstrategy for cleaning a surface to be cleaned of a motor vehicle, for aresource efficient cleaning of at least one surface of a motor vehicle,a cleaning system and a motor vehicle.

The number of sensors being installed in a motor vehicle has also risenas a result of the recent steady expansion of driver assistance systems.

In many modem motor vehicles, sensors support the driver of a motorvehicle within the framework of safety functions, for example in therecognition of obstacles, preferably also in the recognition ofpedestrians, and/or within the framework of semi-autonomous orautonomous motor vehicle operation.

For functional sensor operation and thus also for the continuedoperation of these safety functions and/or for (partially) autonomousvehicle operation, these sensors are dependent on a surface that is notexcessively dirty, so that the increase in the number of sensors hasalso been accompanied by an increase in the need for cleaning.

Cleaning the sensor surfaces requires resources such as water,detergents, energy, etc., but these can only be stored or carried in thevehicle to a limited extent. As a result, there is an increasing demandfor a resource-saving cleaning process.

In addition, the increase in the number of sensors installed in a motorvehicle has led to a situation in which some data can be acquiredredundantly by several sensors, although the failure of one sensorusually also leads to the failure of a driver assistance system.

If resources are to be conserved, the question arises as to whichcleaning strategy can maintain the functionality of the driverassistance systems for as long as possible without having to refillcleaning resources and/or which sensors can possibly be neglected duringcleaning or cleaned with fewer resources.

Thus, the decision making process of cleaning the appropriate sensoradequately is becoming more complex. There are many influences thatdetermine an adequate clean and how this is achieved.

State of the art cleaning of the front and/or rear windscreen of motorvehicles is known, in particular with a windscreen wiper, whereby acleaning fluid may also be applied to the front and/or rear windscreen.

A device for controlling a wiping and/or rinsing system for windscreensis already known from document EP 0 932 533 A1. A sensor device measuresthe wetting or contamination of the windscreen. The wiping and/orrinsing system is switched on when wetting or soiling of the windscreenis detected, as well as when an ignition key is pressed or reverse gearis engaged. This ensures that when the vehicle is started and whenreverse gear is engaged, a clear view through the vehicle windows isensured as a precaution. Depending on the degree of wetting and/or thedegree of soiling, a time period can also be specified for which thewiping and/or rinsing system is switched on.

DE 103 07 216 A1 discloses a process for operating a washer/wiper systemfor a motor vehicle windscreen using at least one windscreen wiper, awasher unit for spraying cleaning fluid onto the windscreen, anelectronic control unit, at least one windscreen wiper motor, and aconveying pump for windscreen cleaning fluid. The wiper speed during thecleaning process is adaptively controlled by the electronic control unitdepending on the driving condition and/or environmental inputparameters.

DE 10 2009 040 993 A1 reveals a device for operating a wiping and/orrinsing system for a windscreen of a vehicle, having a control devicefor controlling a cleaning process of the wiping and/or rinsing system,in which the windscreen of the vehicle can be subjected to a cleaningfluid of the rinsing system and/or a wiper of the wiping system can bemoved in contact with the windscreen relative thereto, wherein thecontrol means is adapted to determine a degree of contamination and/or adegree of wetting of the disc depending on at least one detectedinformation and to set at least one specific parameter of the cleaningprocess depending on the determined degree of contamination and/or thedegree of wetting, wherein the control means is adapted to determine thedegree of contamination and/or the degree of wetting of the disc duringthe cleaning process and to adjust the at least one specific parameterdepending on the degree of contamination and/or the degree of wettingduring the cleaning process, wherein a predetermined plurality of valuecombinations for at least two specific parameters of the cleaningprocess are stored in the control means and the control means is adaptedto select a value combination from the plurality of value combinationsdepending on the degree of contamination and/or the degree of wettingand to adjust the at least two specific parameters according to theselected value combination.

The invention is based on the task of providing the state of the artwith an improvement or an alternative.

According to a first aspect of the invention, the task is solved by acleaning method for a resource efficient cleaning, preferablyresource-saving cleaning, of at least one surface of a motor vehicle,wherein the motor vehicle exhibits a cleaning system and at least onesensor, wherein the sensor is operatively connected to one surface,wherein the cleaning method exhibits at least one cleaning process,wherein the cleaning process is adapted to clean one surface andexhibits a cleaning period comprising a start time and an end time,wherein the cleaning system exhibits an electronic control unit, acleaning fluid distribution system, preferably comprising at least onefluid reservoir, at least one nozzle, and at least one cleaning fluidline, wherein the sensor is adapted to detect at least one measuredquantity, preferably an availability of the sensor, a process quantity,preferably a humidity and/or a temperature in the vicinity of the motorvehicle and/or a rainfall and/or a snowfall quantity and/or a coordinateof the motor vehicle, and/or a control quantity, and to transmit themeasured quantity to the electronic control unit, wherein the nozzle isadapted to bring a cleaning fluid into operative connection with thesurface, wherein the electronic control unit is adapted to controland/or regulate the cleaning process by means of at least one controlquantity of the cleaning process, wherein a resource requirement of thecleaning process depends on a control quantity setpoint,

-   -   characterized in that    -   the electronic control unit controls the resource efficient        cleaning, preferably resource-saving cleaning, depending on a        dependency table exhibiting at least two data sets, preferably        exhibiting at least 50 data sets, particularly preferably        exhibiting at least 200 data sets, wherein each data set        exhibits at least one input quantity of the cleaning system,        preferably a process quantity, preferably a humidity and/or a        temperature in the vicinity of the motor vehicle and/or a        rainfall and/or a snowfall quantity and/or a coordinate of the        motor vehicle, and/or a control quantity and/or a vehicle type        and/or an availability of the sensor, and at least one output        quantity of the cleaning system, preferably the resource        requirement of the cleaning process and/or the availability of        the sensor, stored in an ordered manner with reference to one        another,    -   and/or    -   the electronic control unit controls the resource efficient        cleaning, preferably resource-saving cleaning, depending on a        systematic dependence for a system behaviour of the cleaning        system, particularly for the system behaviour of the cleaning        process of the surface of the motor vehicle, between an input        quantity of the cleaning system, preferably the at least one        control quantity of the cleaning process and/or the at least one        process quantity, preferably a humidity and/or a temperature in        the vicinity of the motor vehicle and/or a rainfall and/or a        snowfall quantity and/or a coordinate of the motor vehicle,        and/or a vehicle type and/or an availability of the sensor, and        an output quantity of the cleaning system, preferably the        resource requirement of the cleaning process and/or the        availability of the sensor, in particular depending on a        systematic dependence derived by a method for indirectly        deriving a systematic dependence for a system behaviour of a        cleaning system of a motor vehicle according to the second        aspect of the invention,    -   and/or    -   the electronic control unit controls the resource efficient        cleaning, preferably resource-saving cleaning applying a control        quantity setpoint, particularly preferably applying a control        quantity setpoint derived by a method according to the third        aspect of the invention,    -   and/or    -   the electronic control unit controls the resource efficient        cleaning, preferably resource-saving cleaning applying a        cleaning strategy, particularly preferably applying a cleaning        strategy derived by a method according to the fourth aspect of        the invention,    -   and/or    -   the cleaning method comprises a process step for indirectly        deriving a systematic dependence for a system behaviour of a        system component of a cleaning system of a motor vehicle,        preferably a process step for indirectly deriving a systematic        dependence according to the fifth aspect of the invention,    -   and/or    -   the cleaning method comprises a process step for diagnosing a        system behaviour of a system component of a cleaning system of a        motor vehicle, preferably a process step for diagnosing a system        behaviour of a system component of a cleaning system according        to the first alternative of the sixth aspect of the invention,    -   and/or    -   the cleaning method comprises a process step for diagnosing a        deviation between an actual system behaviour and an expected        system behaviour of a system component of a cleaning system of a        motor vehicle, preferably a process step for diagnosing a        deviation between an actual system behaviour and an expected        system behaviour of a system component of a cleaning system        according to the second alternative of the sixth aspect of the        invention,    -   and/or    -   the cleaning method comprises a process step for selecting a        resolution strategy, preferably a process step for selecting a        resolution strategy according to the seventh aspect of the        invention,    -   and/or    -   the cleaning method comprises a process step for using of a        selected resolution strategy, preferably a process step for        using of a selected resolution strategy according to the eighth        aspect of the invention,    -   and/or    -   the cleaning method comprises a process step for indirectly        deriving a systematic dependence for a system behaviour of a        soiling process of a surface of a motor vehicle, preferably a        process step for indirectly deriving a systematic dependence        according to the ninth aspect of the invention,    -   and/or    -   the cleaning method comprises a process step for using—        -   a dependency table exhibiting at least two data sets,            preferably exhibiting at least 50 data sets, particularly            preferably exhibiting at least 200 data sets, wherein each            data set exhibits at least one input quantity of the soiling            process, in particular the distance travelled by the motor            vehicle between the first availability and the second            availability and/or the operating time by covering the            distance travelled by the motor vehicle between the first            availability and the second availability, and/or a driving            speed of the motor vehicle, preferably a course of the            driving speed along the route between the first availability            and the second availability, and/or a process quantity,            preferably a humidity, particularly preferably a course of            the humidity along the route between the first availability            and the second availability, and/or a temperature in the            vicinity of the motor vehicle, particularly preferably a            course of the temperature along the route between the first            availability and the second availability, and/or a rainfall,            particularly preferably a course of the rainfall along the            route between the first availability and the second            availability, and/or a snowfall quantity, particularly            preferably a course of the snowfall quantity along the route            between the first availability and the second availability,            and/or a vehicle type and/or a coordinate of the motor            vehicle, preferably the coordinate of the motor vehicle            along the route between the first availability and the            second availability, and/or the first availability of the            sensor, and the evaluated change of availability, stored in            an ordered manner with reference to one another,        -   and/or        -   a systematic dependence for a system behaviour of a soiling            process of a surface of a motor vehicle, preferably derived            by a method for indirectly deriving a systematic dependence            according to the ninth aspect of the invention, for a            resource efficient cleaning, preferably resource-saving            cleaning, of at least one surface of a motor vehicle,    -   to/for    -   determine an expected availability at a distance or an operating        time of the motor vehicle yet to be covered, preferably        according to the tenth aspect of the invention,    -   and/or    -   determine an expected distance or an expected operating time of        the motor vehicle yet to be covered when reaching a threshold of        availability, preferably according to the eleventh aspect of the        invention,    -   and/or    -   optimizing a resource requirement for a cleaning process of a        surface of a motor vehicle, in particular by applying a method        for optimizing a resource requirement for a cleaning process of        a surface of a motor vehicle according to the third aspect of        the invention,    -   and/or    -   determine a cleaning strategy for cleaning a surface to be        cleaned of a motor vehicle, in particular by applying a method        for determining a cleaning strategy for cleaning a surface to be        cleaned of a motor vehicle according to the fourth aspect of the        invention,    -   and/or    -   determine a necessary expected gain in availability, whereby the        sum of the actual availability and the necessary expected gain        in availability is sufficient to achieve a distance or an        operating time yet to be covered by the motor vehicle in such a        way that a threshold of availability is not exceeded, preferably        according to the fourteenth aspect of the invention.

The following terms are explained in more detail:

First of all, it should be expressly pointed out that in the context ofthis patent application indefinite articles and figures such as “one”,“two”, etc. should normally be understood as “at least” information,i.e. “at least one . . . ”, “at least two . . . ”, etc., unless it isexpressly apparent from the respective context or it is obvious ortechnically mandatory for the person skilled in the art that only“exactly one . . . ”, “exactly two . . . ”, etc. can be meant.

In the context of this patent application, the term “in particular”should always be understood as meaning that this term introduces anoptional, preferential feature. The expression is not to be understoodas “namely”.

A “cleaning method” is a method of cleaning at least one surface orcomponent of a surface of a motor vehicle, in which impurities are to bereduced or removed. Preferably, the cleaning method is carried outautomatically or semi-automatically, whereby the driver of the motorvehicle can preferably select a cleaning mode in an automatic cleaningmethod and, if necessary, is requested to replenish resources requiredfor the cleaning method.

In particular, a cleaning procedure may be carried out and/or startedmanually, in particular by the driver of a motor vehicle.

Particularly preferred, it is also conceivable that the cleaning methodmay be carried out automatically during the operation of the vehicleand/or outside the operating time of the vehicle in order to clean atleast one component of a surface of the vehicle and may therefore runautonomously, apart from replenishing any resources required.

Cleaning is understood as the use of cleaning means for cleaning such aswater, air, detergent and/or a wiping element and/or a mechanicalcleaning element and/or a vibration-based cleaning element and/or anultrasonic-based cleaning element to clean a surface. In particular,cleaning does not mean achieving an absolutely clean surface, but theuse of cleaning means to reduce the contamination of a surface.

A “cleaning fluid” is any fluid that can be used as a cleaning means,preferably water, air, a cleaning agent or the like.

A cleaning method preferentially uses one or more “cleaning processes”,whereby a cleaning process concerns the cleaning of one surface. Eachcleaning process exhibits a “cleaning period” in which at least onecleaning means is brought into operative connection with thecorresponding surface, whereby a cleaning period exhibits a “start time”and an “end time”.

Among other things, an end time of a cleaning process should also beunderstood as the end time of a valuation phase of a cleaning process,in particular in the case in which a valuation of the cleaning processis also carried out during the execution of a cleaning process, thepoint of valuation and the cleaning process have a common start time butany deviating end times, preferably the end time of the valuation periodends before the end time of the cleaning process. In any case, the termend time refers to the end time of a cleaning process and/or the endtime of an evaluation process of the cleaning process, depending on thequestion under consideration.

Among other things, it should be specifically considered that a singlecleaning process leads to several data sets in the context of theevaluation of the cleaning process, whereby the different data setspreferably differ only by the end time of the evaluation of the cleaningprocess.

A “surface” is a surface element of a motor vehicle. A preferred termfor a surface is a windshield and/or a rear window and/or a side windowof a motor vehicle. Furthermore, a surface is preferably understood as asurface element behind which a sensor is arranged. Another preferredterm for a surface is a part of the surface of a motor vehicle, which isvisible from the outside, in particular also including a hidden surfacesuch as a part of a wheel arch liner in a wheel arch of a motor vehicle.

A surface can also be understood as a surface element which is locatedinside a motor vehicle, preferably in the interior of the motor vehicleand/or in the engine compartment of the motor vehicle.

A “vehicle” or “motor vehicle” is understood as a self-propelledvehicle, commonly wheeled, that does not operate on rails and is usedfor the transportation of people or cargo.

Preferably, a motor vehicle propulsion is provided by an engine ormotor, usually an internal combustion engine or an electric motor, orsome combination of the two, such as hybrid electric vehicles andplug-in hybrids.

A “cleaning system” is a system that provides all the structuralelements required for the cleaning method and therefore also for thephysical cleaning process.

The cleaning system preferably comprises a cleaning fluid distributionsystem and other electrical and/or electronic components.

A “cleaning fluid distribution system” means a system designed toprovide a cleaning fluid on a surface of a motor vehicle to be cleaned.

Preferably, a cleaning fluid distribution system exhibits at least one“cleaning fluid line” which is adapted to convey a cleaning fluid, inparticular from a pump and/or a cleaning fluid reservoir to a nozzle.

A “nozzle” is a device through which the cleaning fluid can leave thecleaning system and which is designed to bring the cleaning fluid intoan interaction, preferably an operative connection, with the surface tobe cleaned.

Preferably the nozzle is a device designed to control the direction orcharacteristics of the cleaning fluid as it exits the cleaning fluiddistribution system.

Preferably, the nozzle exhibits an actuating means which is designed toinfluence the direction in which the cleaning fluid leaves the cleaningfluid distribution system.

Preferably, the nozzle exhibits a second actuating means which isdesigned to influence the characteristic with which the cleaning fluidleaves the cleaning fluid distribution system, preferably the speed ofthe cleaning fluid.

Preferably a cleaning fluid distribution system is equipped with an“electric pump”, which is designed to pump a cleaning fluid.

A cleaning fluid distribution system comprises a “cleaning fluidreservoir” which is designed to store a cleaning fluid in the motorvehicle. The electric pump is preferably integrated into the cleaningfluid reservoir.

The electric pump is preferably connected to the cleaning fluidreservoir and the nozzle, preferably by means of a “cleaning fluidline”, which is designed to guide the cleaning fluid.

The electronic components of a cleaning system could preferably includean electronic control unit and/or a data processing system. It is alsopossible that the data processing system is integrated into theelectronic control unit.

An “electronic control unit” (ECU) is any embedded system in automotiveelectronics that controls one or more of the electrical systems orsubsystems in a vehicle.

The electronic control unit is preferably set up to carry out thecleaning method, particularly preferably a cleaning method according tothe first aspect of the invention, and/or to carry out a method forindirectly deriving a systematic dependence, preferably a systematicdependence for a system behaviour of a cleaning system of a motorvehicle, particularly preferably for a system behaviour of a cleaningprocess of a surface of the motor vehicle, particularly preferably amethod for indirectly deriving a systematic dependence according to thesecond aspect of the invention, and/or to carry out a method forindirectly deriving a systematic dependence for a system behaviour of asystem component of a cleaning system of a motor vehicle, particularlypreferably a method for indirectly deriving a systematic dependenceaccording to the fifth aspect of the invention, and/or to carry out amethod for indirectly deriving a systematic dependence for a systembehaviour of a soiling process of a surface of a motor vehicle,particularly preferably a method for indirectly deriving a systematicdependence according to the ninth aspect of the invention, and/or tocarry out a method for optimizing a resource requirement for a cleaningprocess of a surface of a motor vehicle, particularly preferably amethod for optimizing a resource requirement according to a first and/orsecond alternative of the third aspect of the invention, and/or to carryout a method for determining a cleaning strategy for cleaning a surfaceto be cleaned of a motor vehicle, particularly preferably a method fordetermining a cleaning strategy according to the fourth aspect of theinvention, and/or to carry out a method for diagnosing a deviationbetween an actual system behaviour and an expected system behaviour of asystem component of a cleaning system of a motor vehicle, particularlypreferably a method for diagnosing a deviation between an actual systembehaviour and an expected system behaviour according to a sixth aspectof the invention, and/or to carry out a method for selecting aresolution strategy, particularly preferably a method for selecting aresolution strategy according to the seventh aspect of the invention,and/or to use a selected resolution strategy, particularly preferably touse a selected resolution strategy according to the eighth aspect of theinvention, and/or to use a dependency table and/or a systematicdependence to determine an expected availability at a distance or anoperating time of the motor vehicle yet to be covered, particularlypreferably to use a dependency table and/or a systematic dependenceaccording to the tenth aspect of the invention, and/or to use adependency table and/or a systematic dependence to determine an expecteddistance or an operating time of the motor vehicle yet to be coveredwhen reaching a threshold of availability, particularly preferably touse a dependency table and/or a systematic dependence according to theeleventh aspect of the invention, and/or to use a dependency tableand/or a systematic dependence for optimizing a resource requirement fora cleaning process of a surface of a motor vehicle, particularlypreferably to use a dependency table and/or a systematic dependenceaccording to the twelfth aspect of the invention, and/or to use adependency table and/or a systematic dependence to determine a cleaningstrategy for cleaning a surface to be cleaned of a motor vehicle,particularly preferably to use a dependency table and/or a systematicdependence according to the thirteenth aspect of the invention, and/orto use a dependency table and/or a systematic dependence to determine anecessary expected gain in availability, particularly preferably to usea dependency table and/or a systematic dependence according to thefourteenth aspect of the invention, and/or to use a systematicdependence derived by a method for indirectly deriving a systematicdependence for a resource efficient cleaning of at least one surface ofa motor vehicle, particularly preferably to use a systematic dependenceaccording to the fifteenth aspect of the invention, and/or to use acontrol quantity setpoint derived by a method for optimizing a resourcerequirement for a cleaning process of a surface of a motor vehicle for aresource efficient cleaning of at least one surface of a motor vehicle,particularly preferably to use a control quantity setpoint according tothe fifteenth aspect of the invention, and/or to use a cleaning strategyderived by a method for determining a cleaning strategy for cleaning asurface to be cleaned of a motor vehicle, for a resource efficientcleaning of at least one surface of a motor vehicle, particularlypreferably to use a cleaning strategy according to the fifteenth aspectof the invention, and/or to be part of a cleaning system according tothe sixteenth aspect of the invention, and/or to be part of a motorvehicle according to the seventeenth aspect of the invention, describedhere.

Furthermore, the electronic control unit is preferably equipped with allstructural electronic elements required for the execution of thecleaning method presented here, preferably the cleaning method accordingto the first aspect of the invention.

Particularly preferred, the electronic control unit comprises a dataprocessing system.

A “data processing system” is a combination of electronic components andelectronic processes that for a set of inputs produces a defined set ofoutputs. The inputs and outputs are interpreted as data.

Preferably, a data processing system is a system that enables theorganized handling of data volumes with the aim of obtaining informationabout these data volumes and/or changing these data volumes.

Preferably, a data processing system exhibits a “data acquisitionsystem”.

A “sensor” or “detector” is a technical component which canqualitatively or as a “measured quantity” quantitatively measure certainphysical or chemical properties and/or the material composition of itsenvironment. These quantities are measured by means of physical orchemical effects and converted into an analogue or digital electricalsignal.

Preferably a sensor exhibits an electronic data processing unit, whichis equipped to process the quantity detected by the sensor, inparticular to a quantity derived from the original measured quantity.

Specifically, it should be considered that such a data processing unitcan determine the state of contamination of a surface operativelyconnected to the sensor, preferably it should be able to determine theavailability of a sensor, and/or the intensity of rain and/or theintensity of snowfall and/or the intensity of condensation and/or theintensity of hail on the basis of a measured quantity detected by asensor.

Preferably such an electronic data processing unit forms a unit with thesensor or is part of an electronic control unit of a motor vehicle.

A data processing unit of this type is preferably set up to process thequantities recorded by several sensors.

The current value of the measured quantity is an “actual or currentmeasured quantity value” and/or a “current or actual measured quantityvalue”.

In particular, a sensor is also to be understood as a virtual sensor. A“virtual sensor” maps the data of one or more recorded measuredquantities with an imaging function to a certain physical or chemicalproperty and/or the material composition of the environmentqualitatively or quantitatively. A sensor can therefore be both aphysical sensor or a virtual sensor, which qualitatively orquantitatively records a quantity and/or a condition of the surroundingenvironment. In other words, a virtual sensor determines a quantity, inparticular a measured quantity, a control quantity or a processquantity, by means of a mathematical prescription.

Preferably, a sensor is understood as an optical sensor.

Preferably, an optical sensor is understood as a camera and/or a lidarand/or a radar and or an ultrasonic sensor.

An optical sensor can preferably determine a brightness level, or inother words a light intensity level.

In particular, it should be considered that by evaluating a lightintensity level, an availability of the sensor can be determined,preferably in comparison with a light intensity level of a second sensorwhose field of view overlaps the field of view of the sensor.

In particular, a sensor also includes a temperature sensor, a pressuresensor, a voltage sensor, a current consumption sensor, a radar sensor,an ultrasonic sensor, a flow rate sensor and the like.

A “measured value” is the current or in other words actual value of a“measured quantity”. A “measured quantity setpoint” is the default valuefor a measured quantity. Preferably, a measured quantity is any quantitythat can be measured or otherwise determined in such a way that themeasured value of the measured quantity can be further processedelectronically. In particular, a measured quantity is understood to be acontrol quantity, a process quantity or a quantity that describes theavailability of a sensor.

Preferably a measured quantity is a vehicle speed.

Preferably, the measured value of a measured quantity can be determinedexperimentally and/or numerically. In the case of an experimentalinvestigation of the measured value of a measured quantity, anexperimental investigation of an entire motor vehicle, preferably in thelaboratory or during regular motor vehicle operation, or of a module ora component within the framework of a module test bench, could beconsidered. In a numerical investigation the measured value of ameasured quantity, numerical analysis within the framework of a physicalmodel and/or a numerical simulation should be considered, whereby theentire vehicle or a module or component can also be consideredseparately.

A measured quantity can also be understood as a quantity that representsdata, whereby this is also referred to as a “data representing measuredquantity”. Data are preferably retrievable data, preferably wirelesslyavailable data, preferably the weather in the vicinity and/or on theplanned route and/or the current coordinate or actual coordinate of themotor vehicle. Furthermore, it is preferable to consider data as asensor type, a vehicle type, a date of the last inspection of a sensorand/or the cleaning system and/or the vehicle and/or the like.

Measured value, measured quantity and measured quantity setpoint are notto be understood as purely scalar quantities or values but whenever thisappears technically reasonable, a measured value, a measured quantityand a measured quantity setpoint should be understood as a vectorialquantity with a plurality of values for the respective dimensions of thevectorial quantity.

A “vehicle type” is the concrete configuration of a vehicle. Inparticular, a vehicle type provides information about which surfaces avehicle exhibits, how these surfaces are shaped, and which sensor ishidden behind which surface.

A “process value” is the current value of a “process quantity”. A“process quantity setpoint” is the default value for a “processquantity”. Preferably, a process quantity is to be understood as aquantity which is suitable to influence the cleaning process and thecleaning result, but which cannot itself be influenced.

Preferably, a process quantity and/or a process quantity setpoint and/ora process value is not a purely scalar quantity or value, but rather avectorial quantity with a plurality of values for the respectivedimensions of the vectorial quantity.

Preferably a process quantity is a vehicle speed.

Preferably a process quantity is a system related process quantity,which relates to the behaviour of the system, preferably the behaviourof the cleaning system, which is preferably described by a systematicdependence. In other words, a system related process quantity has adependence on a control quantity of the system.

Preferably a process quantity is an environmental process quantity,which relates to the surrounding environment, preferably the environmentsurrounding the motor vehicle. Examples for an environmental processquantity are ambient temperature in the vicinity of the motor vehicle,humidity in the vicinity of the motor vehicle, air pressure in thevicinity of the motor vehicle, a current amount of rain and/or snowfall,etc.

Among others, a process quantity is understood as an ambient temperaturein the vicinity of the motor vehicle and/or a humidity in the vicinityof the motor vehicle and/or an actual solar radiation and/or a surfacetemperature of the surface to be cleaned.

A process quantity is preferably a quantity that occurs in a cleaningsystem or around the cleaning system and that can be influenced at leastindirectly by an input quantity.

Preferably, a process quantity is an electric current, a powerconsumption, a flow pressure, a time of operation, a fill level signal,a reaction time, a sensing time, a signal of a leaking through sensor, asignal of a flow gauge, a number of actuations, a spray pattern, a heatmonitoring signal, a signal of a debris sensor, a signal of a checkvalve, a signal of a drip sensor, a signal of a distance sensor and/or asignal of a force sensor.

A “control quantity setpoint” is the default value for an actuator whichis set up to adjust a “control quantity”. The current value of thecontrol quantity is an “actual control quantity value”.

Preferably, a control quantity is to be understood as a quantity whichis suitable to influence the cleaning process and the cleaning result,and which is adjusted to control the cleaning method and/or the cleaningprocess, preferably which is controlled to influence the cleaning methodand/or the cleaning process.

Preferably, a control quantity and/or a control quantity setpoint and/ora control value is not a purely scalar quantity or value, but rather avectorial quantity with a plurality of values for the respectivedimensions of the vectorial quantity.

Preferably and in case of a control system, a control quantity setpointis understood as a default value for an actuator which is set up toadjust a control quantity.

Among others, a control quantity is understood as a type of cleaningfluid, in particular water and/or air, and/or a type of cleaning agentand/or a proportion of cleaning agent in the cleaning fluid and/or atemperature of the cleaning fluid and/or a pressure of the cleaningfluid when leaving the nozzle and/or a flow rate of the cleaning fluidand/or a duration of the cleaning process and/or the number of cycles ofa cleaning process and/or a current consumption of the fluid pump and/orthe voltage of the fluid pump.

Particularly preferred, a control of the control quantity is to pursuean objective, preferably the objective of resource-efficient, preferablyresource-saving, cleaning of at least one surface of a motor vehicle.

Preferably, the control of a control quantity pursues a multi-criteriaobjective, whereby a paretooptimal goal achievement is aimed at,preferably a resource-efficient, particularly preferablyresource-saving, cleaning of at least one surface of a motor vehicle atone or more boundary conditions.

An “availability” of a technical system is a measure of the extent towhich a system can fulfil its task.

According to a conceivable variant, an availability specifies whether asystem can fulfill its task or not by means of two acceptable states.

Preferably a surface in the first state is not too dirty and in thesecond state too dirty than the surface from the point of view of asensor and/or from the point of view of the driver of the motor vehiclefulfils its task or not.

According to a preferred variant, an availability also specifies thecharacteristic value according to which a system can fulfill its task.

Particularly preferred, availability can assume values in a rangeexhibiting an interval, whereby one interval limit on reaching meansthat the system can fully fulfill its requirements, and the otherinterval limit on reaching means that the system can no longer fulfillits requirements.

If the availability value ranges between the interval limits, the systemcan still fulfill its requirements, but under more difficult conditions.In particular, the value of availability reflects the degree ofcontamination of the surface of the motor vehicle, preferably the degreeof contamination of the surface, preferably the surface of a sensor,particularly preferably the degree of contamination of the surface of anoptical sensor and/or the driver of the motor vehicle.

Since, as a rule, it can be assumed that the degree of contamination ofa surface increases with the operating time of a motor vehicle untilcleaning, the availability, if reproduced within an interval, canpreferably be interpreted as a measure of how long the technical system,preferably the sensor, has already fulfilled its requirements and/or howlong the technical system, preferably the sensor, can still fulfill itsrequirements, at least in part, until it must be cleaned in order to beable to fulfill its requirements again.

Availability may also preferably have values outside these intervallimits. An availability that is higher than the value of the intervallimit above which the associated sensor can fully fulfill itsrequirements indicates that the sensor can fully fulfill itsrequirements. An availability that is smaller than the value of theinterval limit from which the associated sensor can no longer fulfillits requirements indicates that the sensor can no longer fulfill itsrequirements. In other words, the surface in an operative connectionwith the sensor must then be cleaned by means of a cleaning process sothat the availability can increase again, especially to a value at whichthe sensor can fulfill at least part of its original tasks again,wherein the surface can also be cleaned by a passive cleaning process,such as rain and/or snowfall.

It is expressly pointed out that the availability of a surface should beunderstood to mean both the availability of a surface for the not tooseverely impaired operation of a sensor and the availability of asurface, preferably the degree of purity of a surface, in particular ofa windscreen and/or of a rear window and/or of the like, for a not tooseverely restricted view of the driver of the motor vehicle.

An “actual availability” or in other words current availability is theavailability that prevails at the current time.

An “expected availability” is to be understood as an estimatedavailability, preferably at a certain distance yet to be covered and/ora certain operating time of the vehicle still to be run through.

An expected availability can preferably be determined with an estimationprocedure, preferably according to the tenth aspect of the invention, onthe basis of the current and/or planned conditions, in particular theoperating conditions of the motor vehicle, whereby the expectedavailability represents the availability at a still to be passed pointof the travel route of the motor vehicle.

A “threshold of availability” is to be understood as a threshold valueof an availability. Preferably, the attainment of a threshold ofavailability requires that the surface, which is in an operativeconnection to the sensor whose availability is considered here, shouldbe cleaned.

An “expected gain in availability” is the estimated gain in theavailability of a sensor if the surface operatively connected to thecorresponding sensor is cleaned, preferably with a defined cleaningprocess, especially preferably with a cleaning process defined by acontrol quantity setpoint.

An expected gain in availability or in other words a necessary expectedgain in availability can preferably be derived according to thefourteenth aspect of the invention.

Depending on the situation, a “change of availability” can be understoodas a “gain in availability” and a “loss of availability”. In any case, achange of availability is to be understood as a change in theavailability of a sensor that is operatively connected to a surface.

A “resource” is a source or supply from which a benefit is produced andit has some utility.

Preferably, a resource is understood here as something that can be usedto clean the surface of a vehicle. Specifically, a cleaning fluid and/ora cleaning agent and/or energy and/or a wiping element, preferably awiping element that can be replaced as required, should be consideredhere.

A “resource requirement” is to be understood as the need for a resourcethat is required for a cleaning process, in particular for a cleaningprocess with a defined control quantity setpoint.

“Resource efficient cleaning” means that the cleaning of the surface tobe cleaned is optimised in such a way that the ratio of cleaning benefitto cleaning effort is taken into account. In other words, a resourceefficient cleaning method requires that a control quantity for acleaning process is selected according to the fact that maximum cleaningsuccess can be achieved with minimum effort.

A control quantity setpoint for resource efficient cleaning canpreferably be derived by a method for optimizing a resource requirementfor a cleaning process of a motor vehicle, preferably by a methodaccording to the third aspect of the invention.

A “resource-saving cleaning” is understood to mean that the cleaning ofthe surface to be cleaned is optimised in accordance with the overridingcleaning objective to be achieved, preferably a cleaning objective canlie in the fact that a defined quantity of safety functions of a motorvehicle does not fail due to contamination of a surface, in particularnot due to contamination of a sensor surface, or due tocontamination-induced impairment of a sensor function. A preferredcleaning objective may also be that an autonomy level of a motor vehicledoes not have to be abandoned due to contamination of a surface, inparticular due to contamination of a sensor surface, or due tocontamination-induced impairment of a sensor function.

A cleaning strategy for resource-saving cleaning can preferably bederived by a method for determining a cleaning strategy for cleaning asurface to be cleaned of a motor vehicle, preferably by a methodaccording to the fourth aspect of the invention.

“Control” is understood as the monitoring and possible adjustment of aninput quantity in order to achieve an objective, whereby an adjustmentof an input quantity occurs in particular in response to the occurrenceof a disturbance quantity.

A “disturbance quantity” is an output quantity whose output quantityvalue deviates from the desired output quantity value.

Preferably, a disturbance quantity is an availability.

Preferably, control means the specification of a control quantitysetpoint to achieve a specific objective, in particular to carry out acleaning method for a resource efficient cleaning, preferablyresource-saving cleaning, of at least one surface of a motor vehicle.

Preferably, control is understood as executing a cleaning method,preferably a cleaning method according to the first aspect of theinvention.

The term “regulate” refers to an automated interaction between thecontinuous acquisition of a measured quantity and the control of asystem depending on a specification for the measured quantity. Inparticular, a continuous comparison of the measured quantity and thespecification for the measured quantity takes place.

An “operating condition” of a motor vehicle is the condition of thecurrent use of the motor vehicle.

An active operating condition is preferably understood to mean that themotor vehicle is being used to achieve a goal by means of activeoperation of the motor vehicle, preferably to cover a distance between astarting point and a planned end point.

Preferably, passive operation means that the motor vehicle is currentlyparked.

A “system” is understood as an entity of connected elements that form acommon whole through relationship, connection, interrelation and/orinteraction.

A “system behaviour” is understood as an observable change of a state ora value of a quantity of a state of a system. Preferably, such anobservable change of a state or a value of state quantity of the systemtakes place as a function of a change of a value of an input quantity.

A “dependence”, in particular a “systematic dependence”, describes therelationship of the dependence of one thing on another, preferably thedependence between of an output quantity of a system on an inputquantity of the system. By varying one thing, a causal variation of theother can be achieved. A functional dependence in the mathematical senseis not necessary in this context of a systematic dependence, butpossible.

Preferably a systematic dependence is understood as a description,preferably a mathematical description, of the system behaviour of asystem, preferably a description of the system behaviour of a cleaningsystem.

It should be expressly pointed out that a systematic dependence shouldnot only be understood as a dependency between purely scalar values ofan input quantity and purely scalar values of an output quantity, but ifapplicable also as a multidimensional dependency between thecorresponding number of input quantities considered for the systematicdependence with the respective associated values and the outputquantities dependent on them with the respective associated values.

A “dependency table” is understood as a list of individual experiencesregarding the system behavior, preferably the system behavior of thecleaning system, in the form of data sets, wherein each data setexhibits at least one input quantity, preferably an input quantity ofthe cleaning system, and at least one output quantity, preferably anoutput quantity of the cleaning system, stored in an ordered manner withreference to one another.

Preferably the experiences about the system behaviour are based onsingle documented cleaning processes, which have been collectedpreferably under laboratory conditions and/or on the real motor vehicleand/or during the real motor vehicle operation and/or on the basis of anumerical model, which shall represent the considered system behaviour.

Among other things, a dependency table can thus be advantageous foralready documented experiences to be applied again at a later point intime, in particular by selecting an associated input quantity from thelist of data sets within the dependency table depending on an outputquantity to be achieved.

In other words, a dependency table makes it possible on the one handthat the experience values stored there can always be retrieved andprocessed again, especially for the control of a cleaning process,whereby the input quantities from the dependency table are used tocontrol a cleaning process at least if technically sensible and possiblein the sense of a control quantity setpoint.

On the other hand, the data sets contained in a dependency table can beused as data points for the derivation of a systematic dependence,especially according to a second and/or fifth and/or ninth aspect of theinvention.

An “input quantity” is defined as a quantity with the help of which atargeted intervention in the control or regulating system of a system,preferably a cleaning system, takes place. Its instantaneous value is an“input quantity value”.

Preferably an input quantity is not to be understood as a purely scalarquantity or value but whenever this appears technically reasonable, aninput quantity value and an input quantity should be understood as avectorial input quantity with a plurality of values for the respectivedimensions of the vectorial input quantity.

Preferred is an input quantity a control quantity and/or a datarepresenting measured quantity, particularly preferred the weather inthe vicinity and/or on the planned route and/or the current coordinateof the motor vehicle.

Preferably, in the case of a control system, an input variable ismeasured by a numerical sensor in such a way that the measured variablecorresponds to the default value of the control system.

Preferably, the input quantity contains further data, in particular datathat provide information about the current position of the motor vehicleand/or the planned route of the motor vehicle and/or the covered routeof the motor vehicle and/or the expected weather, in particular thelocal weather at the respective locations of the pre-planned route ofthe motor vehicle, in particular, humidity and/or solar radiation and/ortemperature and/or rainfall and/or snowfall.

Preferably a value of an input quantity can be understood as a pressureof a cleaning fluid.

Preferably, an input quantity value can be understood as a temperatureof a cleaning fluid.

Preferably, an input quantity value can be understood as a mixture of acleaning fluid, in particular the quantity of one or more additives.

Preferably, the value of an input quantity can be understood to include,but is not limited to, a characteristic of a spray pattern, especiallyan oscillating spray pattern and/or a continuous spray pattern and/or apulse-spray pattern and/or an alignment of spray or spray pattern to thesurface to be cleaned.

An “output quantity” is a quantity resulting from a system, especially acleaning system. Its instantaneous value is an “output quantity value”.

Preferably, an output quantity is not to be understood as a purelyscalar quantity or value but whenever this appears technicallyreasonable, an output quantity value and an output quantity should beunderstood as a vectorial output quantity with a plurality of values forthe respective dimensions of the vectorial output quantity.

Preferably, the value of the output quantity depends on the reaction ofa system to an input quantity. The reaction of the system to an inputquantity is determined by the system behaviour and can be described bythe systematic dependence of the system.

Preferred is an output quantity a system related process quantity and/ora resource requirement of a cleaning process and/or an availability,preferably the availability of a surface of a sensor and/or theavailability of a surface, preferably the degree of purity of a surface,in particular of a windscreen and/or of a rear window and/or of thelike.

A “data acquisition system” is used to record physical quantities.Depending on the sensor used, it may preferably have ananalog-to-digital converter and a measured quantity memory or datamemory. The data acquisition system can preferably be set up to acquireseveral measured variables at the same time.

An “electronic data processing and evaluation unit” is an electronicunit that deals with data volumes in an organised manner, with the aimof obtaining information about or modifying such data volumes.Preferably, the data is recorded in data sets, processed by man ormachine according to a specified procedure and output as a result.

A “database” is a system for electronic data management. A preferredtask of the database is to store large amounts of data efficiently,consistently and permanently and to provide required subsets of thestored data in different, demand-oriented representation types for usersand application programs.

Preferably, a database contains a dependency table.

Preferably, a database contains a systematic dependence.

Preferably, a database can be local or decentralized, especially in adata cloud.

Preferably, a remotely managed database can be accessed via wirelessdata transfer so that data can be received from the remotely manageddatabase and data can be transferred to a remotely managed database.

Preferably, a database exhibits functions with which the database canmanage itself.

Preferably a database is part of a working memory of an electronic dataprocessing and evaluation unit.

Among other things, it is conceivable that a database will delete apreviously existing data set when a new data set is entered, inparticular using a dependency table. Preference could be given todeleting the data set that exhibits the greatest Euclidean distance to astatistical mean of the other data sets. Preference could be given todeleting the data set that shows the greatest deviation from asystematic dependence between the data.

A “data set” is understood as a group of continuously connected datafields, whereby a data field preferably exhibits the value of an inputquantity and/or the value of an output quantity.

Preferably, a data set exhibits the first and the second parameter of amethod according to the second aspect and/or the fifth aspect and/or theninth aspect of the invention.

An “algorithm” is an unambiguous instruction to solve a problem or aclass of problems. Preferably, the algorithm consists of a finite numberof defined individual steps. Thus, the individual steps can beimplemented in a computer program for execution, but can also beformulated in human language. Preferably an algorithm supports a problemsolution, because a certain input, preferably an input of data sets, canbe converted into a certain output by means of an algorithm.

A “curve” is understood as a two-dimensional, three-dimensional ormultidimensional relationship between variables. Preferably thesystematic dependence can be in the form of an (n+i)-dimensional curveof m-th order, taking account for an n-dimensional input quantity and ani-dimensional output quantity.

Preferably, a curve is the image of a continuous function from aninterval to a topological space.

A “coefficient of determination” is understood as the proportion of thevariance in the dependent variable that is predictable from theindependent variable.

Preferably, the coefficient of determination provides a measure of howwell observed outcomes are replicated by the model, based on theproportion of total variation of outcomes explained by the model.

A “regression analysis” is understood as a set of statistical processesfor estimating the relationships among variables. It includes manytechniques for modeling and analyzing several variables, when the focusis on the relationship between a dependent variable and one or moreindependent variables. Preferably, regression analysis helps oneunderstand how the typical value of the dependent variable changes whenany one of the independent variables is varied, while the otherindependent variables are held fixed.

Preferably, regression analysis is understood as one of the followinganalytical models: linear regression, simple regression, polynomialregression, generalized linear model, binomial regression or nonlinearregression or the like.

An “optimization process” is understood as maximizing or minimizing afunction by systematically choosing input values from within an allowedset and computing the value of the function.

A “self-learning optimization method” is a class of algorithms that canalso be classified under the generic term “machine learning”. Acorresponding algorithm is characterized by the fact that it learns onthe one hand from examples and on the other hand can generalize thelearned knowledge. Thus such an algorithm generates knowledge fromexperience.

“Optimization” means any process aimed at finding an optimal value, inparticular the optimal value of an input quantity, by maximizing thedegree of achievement of a goal, in particular by minimizing ormaximizing a corresponding objective function and/or by selecting thevalue of an input quantity that is known to enable or indicate the bestachievement of the goal.

In particular, it should be expressly noted that optimization does notnecessarily imply that the exact optimal value of an input quantity isfound.

A “distance” is understood as the distance between two points which hasbeen or will be covered by the motor vehicle or which is planned to becovered.

Preferably, the distance is the shortest distance between two pointsthat can be covered by a motor vehicle.

Preferably, the distance is the fastest connection of two points thatcan be covered by a motor vehicle.

Preferably, the route planning which establishes a distance is carriedout with the help of a navigation system.

An actual availability can be “sufficient to bridge a distance to thenext cleaning process” if it can be used to cover an upcoming or planneddistance before the next cleaning process without falling below apredefined threshold of availability. In other words, the availableavailability in this case is in all probability sufficient so that theplanned distance can be covered to the next cleaning process with themotor vehicle without losing the functionality of a sensor linked to thecorresponding available area.

An “expected distance of the motor vehicle to be covered when reaching athreshold of availability” is the expected distance that can be coveredby the motor vehicle until a predefined threshold of availability isreached.

An “operating time” is the duration of a period of use of the motorvehicle which has already elapsed or is pending or planned.

An actual availability can be “sufficient to bridge an operating time tothe next cleaning process” if it can be used to cover an operating timepending or planned before the next cleaning process without fallingbelow a predefined threshold of availability. In other words, theavailability available in this case is in all probability sufficient sothat the planned operating time can be covered by the motor vehicleuntil the next cleaning process without losing the functionality of asensor linked to the corresponding available area.

An “expected operating time of the motor vehicle to be covered whenreaching a threshold of availability” is the expected operating timethat can be covered by the motor vehicle until a predefined threshold ofavailability is reached.

A “coordinate” is a geographical position of a motor vehicle on earth,which can be an already passed coordinate, an actual or currentcoordinate or a coordinate on a planned route.

Preferably, a coordinate can also be understood as the course of acoordinate on an already completed or planned route.

A “cleaning strategy” is a plan of how a cleaning system will behave inevery conceivable situation. The cleaning strategy therefore completelydescribes the behaviour of the cleaning system.

Preferably, the cleaning strategy contains when and with what intensitywhich surface is to be cleaned.

Preferably a cleaning strategy exhibits a control quantity setpoint foreach selected sensor.

Preferably a cleaning strategy depends on one or more influencingfactors, especially on the actual availability of a sensor.

A “cleaning mode” or also “actual cleaning mode” is a mode of operationof the cleaning system. By selecting a cleaning mode, the manufacturerof a motor vehicle and/or the driver can influence which driverassistance system should not fail due to contamination of a sensor,whereby a selected cleaning mode can also include that no cleaningshould take place. This can directly influence the availability of adriver assistance system.

Since a cleaning mode determines whether a driver assistance system orhow many driver assistance systems are to be protected against failuredue to excessive soiling by cleaning measures, the selection of acleaning mode also determines the number of “selected sensors” for whicha threshold of availability should not be undershot, so that the“selected sensor” can also be indirectly influenced.

Thus a selected cleaning mode also determines the resource consumptionof a cleaning system or in other words the expected remaining range ofthe motor vehicle with the available cleaning resources.

Preferably, there can be one or more cleaning modes, whereby one or morecleaning modes can be selected at the same time.

Preferably a first cleaning mode has the meaning “fully autonomous motorvehicle operation”, which means that the cleaning system takes allnecessary cleaning measures to ensure that an autonomous operation ofthe motor vehicle does not fail due to a contamination of a sensor ofthe motor vehicle.

Preferably a second cleaning mode has the meaning “comfortable motorvehicle operation” which means that the cleaning system takes allnecessary cleaning measures in order not to let a comfortable operationof the motor vehicle fail due to a contamination of a sensor of themotor vehicle. This includes, among other things, that the cleaningsystem maintains the functionality of the driver assistance systemsdistance maintenance, lane keeping, parking assistant, parking assistantand/or trailer assistant by means of all necessary cleaning measures.

Preferably a third cleaning mode has the meaning “motor vehicleoperation which is as safe as possible” which means that the cleaningsystem takes all necessary cleaning measures to ensure that the safeoperation of the motor vehicle does not fail due to contamination of asensor of the motor vehicle. This includes, among other things, that thecleaning system maintains the functionality of the driver assistancesystems pedestrian recognition and/or road user recognition by means ofall necessary cleaning measures.

Preferably a fourth cleaning mode has the meaning “best possible range”which means that the cleaning system only takes those cleaning measureswhich are prescribed by law for the operation of the motor vehicle.

The cleaning mode “best possible range” is preferably used to achievethe best possible range of the motor vehicle with the available cleaningresources.

A “system component” is understood as any component of a cleaningsystem. It should be expressly pointed out that a system component canbe understood as a complete cleaning system as well as a single assemblyof the cleaning system and a single component of the cleaning system.

In particular, the term system component is used in the context of adiagnosis of a cleaning system. Since every physical component of thecleaning system can also be diagnosed by means of at least onediagnostic means, the term system component refers in particular to thecomponent or assembly or the cleaning system which is the object of anobservation and/or analysis related to the diagnosis.

An “electric current” can flow in an electric circuit under certainconditions. Furthermore, an electrical circuit can have a consumer, inparticular a consumer that enables a useful application, preferably inthe form of a system component. A consumer can have a “powerconsumption”, which stands for the demand of energy by the consumer.

A consumer, which enables an electrical application, needs energy to doits work. In concrete terms, it is conceivable that a consumer may havevarying power consumption for the same work performed. The reason forthis can be different operating conditions, in particular a differentambient temperature, and/or ageing effects of the consumer.

Preferably, an electrical current signal indicates information about anelectrical flux, an electrical transients, electrical noise, electricalnoise and the like.

A “fluid pressure” is the pressure in a fluid, in particular in acleaning fluid, whereby the fluid pressure is composed of a static and adynamic component. A local fluid pressure can be measured locally,especially with a pressure sensor.

A “time of operation” is the individual operating time of a systemcomponent.

A “fill level signal” is understood as information that directlydescribes the value of a filling level in a storage container andindirectly the quantity of a substance stored.

A “reaction time” is generally understood to be a period of time betweenaction and reaction, in particular the time between a measure and aneffect of the measure.

A “sensing time” is the time in which a change in a signal can beperceived, in particular the time between the start of a change in thelevel of a storage tank and the end of a change in the level of astorage tank.

A “signal of a flow gauge” is a piece of information provided by a flowgauge that provides information about the amount of liquid flowingthrough a channel in a given unit of time, in particular the amount ofcleaning liquid flowing through the channel.

A “signal of a leaking through sensor” is information provided by aleaking through sensor that provides information about the presence of aleak and/or the quantity of a leak liquid flow. In particular, a leakingthrough sensor could include a sensor attached to a coupling of twofluid channels.

The “number of actuations” is the number of uses of a system component.In particular, the number of pumping operations already carried out witha pump or the number of heating operations already carried out with aheater could be taken into account.

A “spray pattern” is a pattern that a cleaning fluid leaves on thesurface to be cleaned after leaving a wash nozzle.

A “heat monitoring signal” is understood as information provided by aheat monitoring system that provides information about the temperatureof a surface and/or the heat flow over a surface.

A “signal of a debris sensor” is understood as information provided by adebris sensor that provides information about the quantity and/or typeof foreign bodies in a cleaning system.

A “signal of a check valve” is understood as a piece of informationprovided by a check valve that indicates the position of a check valve.

A “signal of a drip sensor” is understood as information provided by adrip sensor that indicates the presence of a liquid and/or the amount ofa liquid and/or the rain intensity and/or the snow intensity.

A “signal of a distance sensor” is understood as information provided bya distance sensor that indicates the distance between the sensor and anobject detected by the sensor.

A “signal of a force sensor” is understood as information provided by aforce sensor that indicates the presence and/or magnitude of an existingforce.

An “actual system behaviour” is an observable system behaviour of asystem component of a cleaning system for a motor vehicle. Preferablythe actual system behaviour can be monitored and/or determined by meansof a measuring system. Preferably the actual system behaviour can bedescribed by an actual output quantity, which is preferably determinedby the measuring system, preferably by sensors.

It should be expressly pointed out that an actual output quantity can beunderstood as a scalar and a vector quantity. If the actual outputquantity has only one parameter, it is a scalar quantity. If the actualoutput quantity has several parameters, in particular a course of aparameter over time, the actual output quantity is a vector quantity.

Preferably, an actual output quantity is designed to describe the systembehaviour of a system component, preferably with all parameters that arerelevant for the characterization of the system behaviour.

An expected system behaviour is the system behaviour of a systemcomponent of a cleaning system for a motor vehicle, which is expected onthe basis of empirical values. Analogous to the actual system behaviourand the actual output quantity, the expected system behaviour can bedescribed with an “expected output quantity”.

It should be explicitly pointed out that the expected output quantitycan also be a scalar or vector quantity analogous to the actual outputquantity.

A “deviation” is the difference between an expected output quantity andan actual output quantity. Thus the deviation can also be a scalar orvector quantity. Preferably the deviation exhibits the dimensionality ofthe actual output quantity.

In particular, a deviation can exhibit a system-typical measurementerror. In particular, this system-typical measurement error can vary insize according to any dimension of the deviation, whereby the size ofthe measurement error can depend in particular on the measurement systemused to determine the output quantity.

If the deviation is in the range of the specified measurement error, anumerical deviation is present, but in this case the actual systembehaviour preferably does not deviate from the expected systembehaviour.

The system behaviour of a system component of a cleaning system for amotor vehicle can be subject to a measurement error and furtherfluctuations and/or deviations which may lie within an expected range.These expected uncritical deviations and/or fluctuations can bedifferent for each dimension of the output quantity.

A “temporal course”, in particular a temporal course of a deviation, isa data series as a function of time, in particular a data series withdata of a deviation.

A data series can consist of at least two, preferably at least 10 andpreferably at least 20 data points distributed over time.

Preferably, the data points have an equidistant time distance to eachother.

Preferably, the time interval between the data points increases.Especially preferred is the time distance of the data pointsproportional to one by the logarithm from time.

A “step response” is an output signal of a system, in particular anoutput signal of a system component of a cleaning system, which reactsto the planned change of an input quantity. Preferably it can be usedadvantageously for the characterization of linear time-invariantsystems. Preferably, the temporal course of a step response can be usedto draw conclusions about the attenuation present in the system, wherebyit can be advantageously determined, for example, whether, inparticular, a blocking of a flow channel for cleaning fluid is presentor not.

A “drift” is a systematic deviation that continuously changes in onedirection.

Preferably a drift of the output signal of a system component can enablea statement about an ageing phenomenon of the system component. A driftcan be used in particular to determine how long the system component canstill be used. In particular, a drift can be used to analyse when thesystem component should be replaced in order to avoid failure of thesystem component.

Overall, a system behaviour of a system component preferably deviatesfrom the tolerated system behaviour only when the output quantityexceeds an “upper threshold quantity” and/or falls below a “lowerthreshold quantity”, taking into account any measurement errors andexpected uncritical fluctuations.

It should be expressly pointed out that an upper threshold quantityand/or a lower threshold quantity can be a scalar or vector quantityjust like the expected output quantity or the actual output quantity orthe deviation. Preferably an upper threshold quantity and/or a lowerthreshold quantity exhibits the dimension of the output quantity.

Preferably, this is a non-tolerated deviation if an output quantityexceeds an upper threshold quantity in one dimension or falls below alower threshold quantity in one dimension.

Preferably the upper threshold value and the lower threshold value candepend on the input quantity, since the system behaviour of a systemcomponent depends on the input quantity in some cases, whereby in somecases also an expected system behaviour of a system component and/or areversible range of the actual output quantity can depend on the inputquantity.

By “diagnosing” is generally understood a comparison between an observedand an expected system behaviour of a system component of a cleaningsystem.

In particular, “diagnosing” means a process that monitors an outputquantity and determines whether or not the system behaviour of theobserved system component deviates from the expected system behaviour ina tolerable range, in particular by comparing the output quantity withan upper threshold quantity and/or a lower threshold quantity.

Likewise, a non-tolerated deviation of an actual system behaviour canpreferably be evaluated on the basis of a percentage limit valuedepending on the expected output quantity.

Diagnosing can preferably also be understood as a characterization of apossible deviation. This characterisation can preferably be carried outon the basis of the temporal course of an output quantity.

A “diagnosing signal” preferably describes the result of a method fordiagnosing a system behaviour of a system component of a cleaning systemof a motor vehicle.

Among other things, a diagnostic signal can indicate that the actualsystem behavior fully corresponds to an expected system behavior.

A diagnosing signal can also indicate that the actual system behaviordoes not correspond to an expected system behavior, whereby thediagnosing signal preferably also contains in which form and on thebasis of which components of the output quantity the actual systembehavior does not correspond to the expected system behavior.

A “present diagnostic signal” is understood as a diagnostic signal whichis currently present and for which a resolution strategy is searched.

A “resolution strategy” is understood as a procedure, which according toavailable empirical values is suitable for eliminating a deviationbetween an actual system behaviour of a system component and an expectedsystem behaviour of this system component of the cleaning system.

A “soiling process” is understood as the accumulation of contaminationand/or pollution on a surface.

A “soiling condition” is understood as the current state ofcontamination and/or contamination on a surface.

A “first availability” is understood as a first state of anavailability. A “second availability” is understood to be a second stateof availability, where time has elapsed between a first availability anda second availability.

Preferably, a motor vehicle has travelled between a first availabilityand a second availability.

Preferably, a motor vehicle has increased its operating time between afirst availability and a second availability.

Due to the increase in the number of driver assistance systems, thenumber of sensors in a vehicle has also increased, in particular thenumber of sensors with an optical operating principle. In particular,sensors with an optical active principle depend on the fact that thepart of the surface of a motor vehicle which is in an active connectionwith a sensor, in particular in an active connection with a sensor withan optical active principle, may only exhibit an upper limit ofcontamination.

If the contamination of this part of the surface of the motor vehicle isabove this maximum contamination, the functionality of the sensor can nolonger be guaranteed to a sufficiently high degree, whereby thefunctionality of the driver assistance system is also influenced by thecontamination condition.

The consequence of this is that the maintenance of the functionality ofa driver assistance system requires cleaning of the surface being in anactive connection with a respective sensor delivering data for a driverassistance system, which has also increased with the increasing numberof sensors.

For this cleaning effort sufficient cleaning resources are needed,especially cleaning fluid and electricity. An increase in the need forcleaning therefore also increases the need for cleaning fluid, whichmust be stored in a motor vehicle to clean the relevant surfaces. Thisleads to an increasing space requirement for a cleaning fluid reservoirand furthermore to an increased weight of the motor vehicle.

Neither additional weight nor additional space requirements for systemcomponents are desirable.

For this reason, a specific cleaning method for resource efficientcleaning, preferably resource-saving cleaning, of at least part of thesurface of a motor vehicle is proposed here.

Resource efficient cleaning means that the cleaning of the surface to becleaned is optimised in such a way that the ratio of cleaning effect tocleaning expenditure is taken into account. In other words,resource-efficient cleaning requires that a control quantity for acleaning process is selected in such a way that maximum cleaning successcan be achieved with minimum effort, whereby the control quantitysetpoint at least indirectly determines the amount of resources that acleaning process requires to clean a surface.

A resource-saving cleaning is understood to mean that the cleaning ofthe surface to be cleaned is optimised in accordance with the overridingcleaning objective to be achieved, preferably a cleaning objective canlie in the fact that a defined quantity of safety functions of a motorvehicle does not fail due to contamination of a surface, in particularnot due to contamination of a sensor surface, or due tocontamination-induced impairment of a sensor function. A preferredcleaning objective may also be that an autonomy level of a motor vehicledoes not have to be abandoned due to contamination of a surface, inparticular due to contamination of a sensor surface, or due tocontamination-induced impairment of a sensor function.

The cleaning method proposed here uses a cleaning system of a motorvehicle and plans and/or optimises and/or executes individual cleaningprocesses, whereby each individual cleaning process concerns thecleaning of an individual partial surface of a motor vehicle through theuse of cleaning means, in particular cleaning fluid and the like.

Each cleaning process also exhibits a time span in which the cleaningprocess is executed, whereby the cleaning process exhibits a start timeand an end time of this time span.

The cleaning system exhibits an electronic control unit, a cleaningfluid distribution system, preferably comprising at least one fluidreservoir, at least one nozzle, and at least one cleaning fluid lineconnecting the cleaning fluid reservoir and the wash nozzle.

The cleaning success is recorded at least partially automatically withinthe scope of the cleaning method proposed here, in that the sensor,which is in an active connection with the surface to be cleaned, ispreferably capable of or is arranged to forward an availability of thesensor to the cleaning system, wherein the availability of the sensor atleast indirectly represents a measure of the cleaning state of thesurface, which is in an active connection with the sensor.

Furthermore, it is suggested that the cleaning system can access or haveavailable information on the availability of a sensor and thus on thecleaning status of a surface to be cleaned in an active connection withthe sensor.

Furthermore, a sensor may be arranged to detect a process quantity, inparticular a humidity and/or a temperature in the vicinity of the motorvehicle and/or a rainfall and/or a snowfall quantity.

The cleaning system may have further sensors or be connected to furthersensors which can provide the cleaning system with a measured quantity,in particular a process quantity and/or a control quantity. In this way,the temperature or the rain quantity or the like can also be madeavailable to the cleaning system by other sensors. This also includesthe transmission of corresponding data to the cleaning system, which themotor vehicle can retrieve via a wireless data connection if necessary.

In particular, the cleaning system can also be provided with thecoordinates of the motor vehicle and or a control value of a controlquantity.

In particular, a cleaning method should be considered which usesinformation about the system behaviour of a cleaning system and/or whichcan provide this information itself, in particular by means of adependency table and/or a systematic dependence, in particular by meansof a dependency table and/or a systematic dependence according to thesecond aspect of the invention.

It is understood that the advantages of a dependency table and/or asystematic dependence according to the second aspect of the invention,as described in the second aspect of the invention, directly extend to acleaning method according to the first aspect of the invention, whichapplies a dependency table and/or a systematic dependence according tothe second aspect of the invention and/or carries out a procedure forderiving a dependency table and/or a systematic dependence according tothe second aspect of the invention.

Furthermore, a cleaning method is proposed which controls the resourceefficient cleaning, preferably resource-saving cleaning applying acontrol quantity setpoint, particularly preferably applying a controlquantity setpoint derived by a method according to the third aspect ofthe invention.

It is understood that the advantages of a control quantity setpointaccording to the third aspect of the invention, as described in thethird aspect of the invention, directly extend to a cleaning methodapplying such control quantity setpoint according to the first aspect ofthe invention.

In addition, a cleaning method is proposed which controls the resourceefficient cleaning, preferably resource-saving cleaning applying acleaning strategy, particularly preferably applying a cleaning strategyderived by a method according to the fourth aspect of the invention.

It is understood that the advantages of a cleaning strategy according tothe fourth aspect of the invention, as described in the fourth aspect ofthe invention, directly extend to a cleaning method applying suchcleaning strategy according to the first aspect of the invention.

In particular, a cleaning method should be considered which usesinformation about the system behaviour of a system component of acleaning system and/or which can provide this information itself, inparticular by means of a dependency table and/or a systematicdependence, in particular by means of a dependency table and/or asystematic dependence according to the fifth aspect of the invention.

It is understood that the advantages of a dependency table and/or asystematic dependence according to the fifth aspect of the invention, asdescribed in the fifth aspect of the invention, directly extend to acleaning method according to the first aspect of the invention, whichapplies a dependency table and/or a systematic dependence according tothe fifth aspect of the invention and/or carries out a procedure forderiving a dependency table and/or a systematic dependence according tothe fifth aspect of the invention.

In particular, a cleaning method should also be considered whichcomprises a process step for diagnosing a system behaviour of a systemcomponent of a cleaning system of a motor vehicle, preferably a processstep for diagnosing a system behaviour of a system component of acleaning system according to the first alternative of the sixth aspectof the invention.

It is understood that the advantages of a method diagnosing a systembehaviour of a system component of a cleaning system according to thefirst alternative of the sixth aspect of the invention, as described inthe first alternative of the sixth aspect of the invention, directlyextend to a cleaning method which comprises such process step fordiagnosing a system behaviour of a system component of a cleaning systemof a motor vehicle according to the first aspect of the invention.

In particular, a cleaning method should also be considered whichcomprises a process step for diagnosing a deviation between an actualsystem behaviour and an expected system behaviour of a system componentof a cleaning system of a motor vehicle, preferably a process step fordiagnosing a deviation between an actual system behaviour and anexpected system behaviour of a system component of a cleaning system ofa motor vehicle according to the second alternative of the sixth aspectof the invention.

It is understood that the advantages of a method diagnosing a deviationbetween an actual system behaviour and an expected system behaviour of asystem component of a cleaning system of a motor vehicle according tothe second alternative of the sixth aspect of the invention, asdescribed in the second alternative of the sixth aspect of theinvention, directly extend to a cleaning method which comprises suchprocess step for diagnosing a deviation between an actual systembehaviour and an expected system behaviour of a system component of acleaning system of a motor vehicle according to the first aspect of theinvention.

A cleaning method is also proposed, which comprises a process step forselecting a resolution strategy, preferably a process step for selectinga resolution strategy according to the seventh aspect of the invention.

It is understood that the advantages of a method for selecting aresolution strategy, preferably a method for selecting a resolutionstrategy according to the seventh aspect of the invention, as describedin the seventh aspect of the invention, directly extend to a cleaningmethod applying such method for selecting a resolution strategyaccording to the first aspect of the invention.

Furthermore, a cleaning method should be considered, comprising aprocess step for using of a selected resolution strategy, preferably aprocess step for using of a selected resolution strategy according tothe eighth aspect of the invention.

It is understood that the advantages of a method for using of a selectedresolution strategy, preferably a process step for using of a selectedresolution strategy according to the eighth aspect of the invention, asdescribed in the eighth aspect of the invention, directly extend to acleaning method applying such method for using of a selected resolutionstrategy according to the first aspect of the invention.

In particular, a cleaning method should be considered which usesinformation about the system behaviour of a soiling process of a surfaceof a motor vehicle and/or which can provide this information itself, inparticular by means of a dependency table and/or a systematicdependence, in particular by means of a dependency table and/or asystematic dependence according to the ninth aspect of the invention.

It is understood that the advantages of a dependency table and/or asystematic dependence according to the ninth aspect of the invention, asdescribed in the ninth aspect of the invention, directly extend to acleaning method according to the first aspect of the invention, whichapplies a dependency table and/or a systematic dependence according tothe ninth aspect of the invention and/or carries out a procedure forderiving a dependency table and/or a systematic dependence according tothe ninth aspect.

In particular, within the cleaning method proposed here, one shouldconsider using a dependency table and/or a systematic dependenceaccording to the ninth aspect of the invention, to determine an expectedavailability at a distance or an operating time of the motor vehicle yetto be covered, preferably according to the tenth aspect of theinvention, and/or to determine an expected distance or an expectedoperating time of the motor vehicle yet to be covered when reaching athreshold of availability, preferably according to the eleventh aspectof the invention, and/or for optimizing a resource requirement for acleaning process of a surface of a motor vehicle, in particular byapplying a method for optimizing a resource requirement for a cleaningprocess of a surface of a motor vehicle according to the third aspect ofthe invention, and/or to determine a cleaning strategy for cleaning asurface to be cleaned of a motor vehicle, in particular by applying amethod for determining a cleaning strategy for cleaning a surface to becleaned of a motor vehicle according to the fourth aspect of theinvention, and/or to determine a necessary expected gain inavailability, whereby the sum of the actual availability and thenecessary expected gain in availability is sufficient to achieve adistance or an operating time yet to be covered by the motor vehicle insuch a way that a threshold of availability is not exceeded, preferablyaccording to the fourteenth aspect of the invention.

It is understood that the advantages of using a dependency table and/ora systematic dependence according to the ninth aspect of the invention,to determine an expected availability at a distance or an operating timeof the motor vehicle yet to be covered, preferably according to thetenth aspect of the invention, and/or to determine an expected distanceor an expected operating time of the motor vehicle yet to be coveredwhen reaching a threshold of availability, preferably according to theeleventh aspect of the invention, and/or for optimizing a resourcerequirement for a cleaning process of a surface of a motor vehicle, inparticular by applying a method for optimizing a resource requirementfor a cleaning process of a surface of a motor vehicle according to thethird aspect of the invention, and/or to determine a cleaning strategyfor cleaning a surface to be cleaned of a motor vehicle, in particularby applying a method for determining a cleaning strategy for cleaning asurface to be cleaned of a motor vehicle according to the fourth aspectof the invention, and/or to determine a necessary expected gain inavailability, whereby the sum of the actual availability and thenecessary expected gain in availability is sufficient to achieve adistance or an operating time yet to be covered by the motor vehicle insuch a way that a threshold of availability is not exceeded, preferablyaccording to the fourteenth aspect of the invention, as described in theninth and/or tenth and/or eleventh and/or twelfth and/or thirteensand/or fourteenth aspect of the invention, directly extend to a cleaningmethod using such dependency table and/or such systematic dependence asdescribed above according to the first aspect of the invention.

In an expedient embodiment the electronic control unit controls and/orregulates the resource efficient cleaning, preferably resource-savingcleaning, depending on an actual measured quantity value, preferably anactual availability of the sensor which is operatively connected to thesurface to be cleaned.

Here it is now specifically proposed, among other things, that thecleaning method should be implemented in a regulated manner.

In other words, the cleaning method should not only be controlledaccording to a specification, but should also be applied within theframework of a regulation.

The cleaning method should be regulated as a function of a measuredquantity, in particular as a function of the availability of the sensorwhose surface is in an active connection with it and is currently beingcleaned by means of a cleaning process as part of the cleaning method.

In other words, it is concretely proposed to regulate each individualcleaning process carried out within the scope of the cleaning method onthe basis of the availability of the associated sensor.

This is an advantage in that it is possible to react to deviations inthe cleaning result according to the situation by feedback ofinformation on the current cleaning status, in particular by means ofavailability of the associated sensor.

This allows an effective cleaning process to be aborted earlier thanplanned, thus saving additional resources and preventing over-cleaningof a surface to be cleaned.

Furthermore, it can be advantageously achieved that a less effectivethan expected cleaning process can be carried out longer than planned,whereby a resource-optimal cleaning result can be achievedadvantageously with an overall evaluation, even if additional resourceshave to be used for this individual cleaning process, resources canstill be saved in total.

Preferably the cleaning method starts a cleaning process as soon as apredefined threshold of availability for the sensor is reached, which isin an active connection with the surface to be cleaned by the cleaningprocess, preferably if the respective surface is not currently excludedfrom cleaning by means of the cleaning strategy.

Here it is proposed that a cleaning process, especially a cleaningprocess pre-planned by means of a control quantity setpoint, is starteddepending on the occurrence of a triggering condition, especially assoon as a predefined threshold of availability for the sensor isreached.

In this way, it can be advantageously achieved that resources forcleaning can be saved, since a cleaning process never starts earlierthan is technically necessary.

Furthermore, it is proposed that the cleaning method starts a cleaningprocess if the availability of a sensor is less than a predefinedthreshold of availability for the sensor or close to a predefinedthreshold of availability for the sensor.

Among other things, this can be advantageous for the cleaning method tostart a cleaning process even after a malfunction of the cleaning systemand/or after a replenishment of previously insufficient cleaningresources, in particular to start an overdue cleaning process.

In particular, it should preferably be considered that the cleaningmethod described here is applied for all surfaces in active connectionwith a sensor and/or for the surfaces in active connection with a sensorrequired/selected according to the current cleaning mode and/or for thesurfaces in active connection with a sensor required/selected accordingto a preselected future cleaning mode.

Expediently the cleaning method forces a change in a cleaning mode if itis not realistic to achieve the planned route with the currentlyselected cleaning mode.

If the pre-planned destination can no longer be reached with thepre-selected cleaning mode, it is proposed to change the cleaning modein such a way that the cleaning mode with which the pre-planned routecan still be carried out without further necessary changes to thecleaning mode is re-selected, whereby the cleaning mode can be selectedwhich, subject to compliance with the above condition, enables thedriver to have the most comfortable possible driving experience.

The advantage of this is that a planned destination can be reached withthe available resources for cleaning under the most comfortableconditions possible for the driver, without having to replenish cleaningresources during a service stay.

In particular, it should preferably be considered that the cleaningmethod described here is applied for all surfaces in active connectionwith a sensor and/or for the surfaces in active connection with a sensorrequired/selected according to the current cleaning mode and/or for thesurfaces in active connection with a sensor required/selected accordingto a preselected future cleaning mode.

In an expedient embodiment the cleaning method goes over to keeping onlya sensor absolutely necessary for manual driving sufficiently availableby carrying out a corresponding cleaning process, if a cleaning resourcehas reached a reserve level.

A kind of reserve strategy is proposed here as a measure of the lastmoment, whereby in the case in which the attainment of a pre-planneddestination without service maintenance is endangered and whereby thecleaning mode was not adapted to a lower level of cleaning resourceconsumption at an early stage, that the cleaning mode is changed by thecleaning system to such an extent that only the sensors that areabsolutely necessary for manual driving remain sufficiently available.

Optionally it is proposed to take this measure as late as possible, sothat with the last available cleaning resources the destination of thetravel route can just be reached.

The advantage of this is that the driver can only be forced to intervenemore in the driving of the motor vehicle as late as absolutelynecessary.

Furthermore, it is proposed as a modification according to a furtheroptional embodiment to moisten the surface which is only in an effectiveconnection with an unnecessary sensor from time to time with a spray ofa cleaning fluid.

In this way, it can be advantageously achieved that a surface that isnot in an active connection with one of the necessary sensors does notdry out, thus advantageously preventing the incrustation of thecontamination present on this surface. In this way it can beadvantageously achieved that another cleaning process aimed at thedirect cleaning of the surface can get by with less cleaning resources,since it does not have to remove an encrusted layer of dirt in a shorttime, but rather an already soaked or pre-soaked dirt.

In other words, no cleaning process is proposed here in particular,which is aimed at the immediate cleaning of the surface, but a cleaningprocess, which makes it easier for a later cleaning process aimed at theimmediate cleaning of the surface to achieve a better cleaning result,in particular a higher gain of availability, with less resourceexpenditure.

In combination, a more efficient cleaning process can thus be madepossible.

In particular, it should preferably be considered that the cleaningmethod described here is applied for all surfaces in active connectionwith a sensor and/or for the surfaces in active connection with a sensorrequired/selected according to the current cleaning mode and/or for thesurfaces in active connection with a sensor required/selected accordingto a preselected future cleaning mode.

Optionally, the cleaning method exhibits a cleaning process which isadapted to moisten a surface to be cleaned.

Here a cleaning method is proposed, which exhibits a cleaning process,which is designed for moistening a surface to be cleaned.

The cleaning method should preferably exhibit two cleaning processes,whereby the first cleaning process according to a time perspective isdesigned to only moisten the surface so that any encrusted dirt on thesurface to be cleaned is softened. This is an advantage in that it iseasier to dissolve the contamination in a subsequent cleaning process.

The second cleaning process according to a time perspective is designedto reduce or remove the previously softened dirt by using cleaningmeans.

Furthermore, it should be specifically considered that a cleaningprocess set up to clean a surface to be cleaned is preceded by a numberof cleaning processes, each of which is intended to moisten the surfaceto be cleaned. These cleaning processes, which are set up to humidifythe surface, can take place during the active and/or passive operatingstate of the motor vehicle.

In this way, the drying of dirt on a surface to be cleaned can beadvantageously prevented.

It is therefore particularly conceivable that a surface of the motorvehicle to be cleaned can also be moistened in a parked state by meansof a cleaning process.

The advantage is that the overall resource efficiency can be improvedwhen cleaning a surface to be cleaned.

In particular, it should preferably be considered that the cleaningmethod described here is applied for all surfaces in active connectionwith a sensor and/or for the surfaces in active connection with a sensorrequired/selected according to the current cleaning mode and/or for thesurfaces in active connection with a sensor required/selected accordingto a preselected future cleaning mode.

In an optional embodiment the cleaning method exhibits a cleaningprocess which is adapted to start upon a change in an operatingcondition of the motor vehicle.

Here it is suggested that the cleaning method is adapted to start acleaning process when an operating condition of the motor vehiclechanges.

Preferably, it should be considered that the cleaning method starts acleaning process when the motor vehicle is started, i.e. at thetransition from the passive to the active operating state of the motorvehicle, so that the availability of a sensor at the start of thejourney can be improved, in particular in such a way that a sensorachieves a minimum availability for functional sensor operation.

Furthermore, it should also be considered that a cleaning method with achange in the cleaning mode by starting a cleaning process is designedto achieve a minimum availability for functional sensor operation forall sensors required in the newly selected cleaning mode.

The advantage of this is that the cleaning method can react to changesin the operating status of the motor vehicle depending on the situation.

In particular, it should preferably be considered that the cleaningmethod described here is applied for all surfaces in active connectionwith a sensor and/or for the surfaces in active connection with a sensorrequired/selected according to the current cleaning mode and/or for thesurfaces in active connection with a sensor required/selected accordingto a preselected future cleaning mode.

According to a second aspect of the invention, the task is solved by amethod for indirectly deriving a systematic dependence for a systembehaviour of a cleaning system of a motor vehicle, particularly for asystem behaviour of a cleaning process of a surface of the motorvehicle, for cleaning of at least one surface of the motor vehicle,preferably a resource efficient cleaning, particularly preferably aresource-saving cleaning, whereby an output quantity depends on an inputquantity by means of the system behaviour of the system, exhibiting thefollowing steps:

-   -   Determine the input quantity as a first parameter of the method        by means of at least one sensor;    -   Determine the output quantity as a second parameter of the        method, preferably by means of at least one sensor;    -   Digitalize where necessary and record the determined first and        second parameters by a data processing system, whereby the data        processing system exhibits an electronic data processing and        evaluation system and a database;    -   Store the determined first and second parameters in an ordered        manner with reference to one another in the database as a data        set of a dependency table;    -   Derive the systematic dependence between the first and second        parameters by means of the electronic data processing and        evaluation system from at least two data sets of the dependency        table stored in the database, preferably from at least 50 data        sets of the dependency table, particularly preferably from at        least 200 data sets of the dependency table, whereby the        electronic data processing and evaluation unit accesses the data        sets of the dependency table and determines the systematic        dependence from the data sets by means of an algorithm; and    -   Preferably store the derived systematic dependence in the        database and/or the electronic data processing and evaluation        unit and/or an electronic control unit.

Previously, it was common practice for the surfaces of a vehicle to becleaned either at the driver's request, at predetermined intervals orautomatically when contamination was detected.

With the increasing number of sensors in a motor vehicle and theincreased safety aspects resulting from the possibilities offered bydriver assistance systems through to autonomous driving, the relevanceof cleaning the surfaces of a motor vehicle, in particular the surfacessuperimposed on a sensor, has increased significantly.

A surface superimposed on a sensor is defined in particular as theoutermost surface of a motor vehicle which covers a sensor, inparticular a windscreen, a rear window, a camera lens and/or a sensorcover.

As a consequence of the increased need for cleaning, the need forresources to clean the corresponding surfaces has also increased.

This brings the need for new cleaning strategies into focus, whichshould achieve a resource efficient cleaning, preferably aresource-saving cleaning, so that fewer resources have to be providedfor the necessary cleaning processes.

Thus, the connection between the cleaning success of a cleaning processand the resulting resource requirement becomes the attention of theconsiderations, especially with the objective of being able to carry outcleaning as efficiently as possible or even better resource-saving.

Preferably, the cleaning success of a cleaning process can be evaluatedon the basis of the availability of a sensor before and after a cleaningprocess.

The cleaning success is influenced among other things by a differentprocess quantity of the cleaning process, among others by the airhumidity and/or the air temperature and/or the rainfall quantity and/orthe snowfall quantity and/or the actual solar radiation and/or thetemperature of the surface to be cleaned.

Furthermore, the cleaning success is also influenced by the speed atwhich the motor vehicle is travelling during the cleaning process andthe type of the motor vehicle. The vehicle type provides information onhow many surfaces are to be cleaned, where the surfaces to be cleanedare located on the motor vehicle and how they are oriented in relationto the direction of movement of the motor vehicle.

In addition, there is a large number of conceivable cleaning processeswhich differ in the choice of the respective different control quantity.

The control quantity decides when, for how long and in what form whichresource and/or which cleaning means is used to get the respectivesurface cleaned.

The resource requirements of a cleaning process can, among other things,be determined directly or indirectly depending on the control quantityof the cleaning process.

When implementing resource efficient cleaning, preferablyresource-saving cleaning, the concrete question arises as to whichcontrol quantity can be used for which vehicle type, which processquantity and under which resource requirement to achieve which cleaningsuccess.

As already explained above, a large number of influencing quantitiescould be taken into account which influence the result and the resourcerequirements of the cleaning process, thus increasing the complexity ofthe question considered here.

In the recent past it has been shown more and more often that themanifold possibilities to influence the cleaning process in theircomplexity and due to the possible overlapping of the individual effectsamong each other increasingly leave the range in which aresource-efficient cleaning lies in the range of the intuitivelycomprehensible.

A resource-saving cleaning in the sense of a resource-optimized cleaningstrategy is even more complex to handle.

As a consequence, not only the effort involved in designing a cleaningsystem and a cleaning strategy has increased massively, but also theresources required, since successful cleaning must be guaranteed whileguaranteeing a certain level of safety, and this goal can be achievedprimarily by expanding the use of resources.

In this respect, the objective of resource efficient cleaning,preferably resource-saving cleaning, of the surfaces to be cleaned of amotor vehicle is currently a highly discussed topic, in particular,because the comprehensive system behavior between input quantities andoutput quantities is not determined.

This kind of necessary information is complex to obtain and requires alot of effort to obtain.

Deviating from the above, a method for indirectly deriving a systematicdependence for the system behaviour of the cleaning system of the motorvehicle between an input quantity of the system and an output quantityof the system is proposed here, whereby the output quantity depends onthe input quantity by means of the system behaviour of the system.

Preferably, the input quantity exhibits the control quantity of thecleaning method.

Preferably, the input quantity exhibits a pressure of a cleaning fluidand/or a temperature of a cleaning fluid and/or a mixture of a cleaningfluid, in particular the quantity of one or more additives, and/or acharacteristic of a spray pattern, particularly whether a spray patternis an oscillating spray pattern and/or a continuous spray pattern and/ora pulse-spray pattern, and/or an alignment of a spray pattern to thesurface to be cleaned.

Preferably, the input quantity exhibits the process quantity.

Preferably, the output quantity is the cleaning success of the cleaningmethod, which can be evaluated in particular by the difference betweenthe availability of a sensor before and after cleaning the correspondingsurface covering the sensor, in particular by the gain in availability.

Furthermore, it is suggested that the output quantity should show theresource requirement of the cleaning method. The resource requirementcan be determined indirectly, especially as a function of the controlquantity, or directly on the basis of corresponding measured values.

Preferably it is suggested that the systematic dependence describes thesystem behaviour of the cleaning process of the surface of the motorvehicle, for cleaning of at least one surface of the motor vehicle.

The procedure proposed here, in which

-   -   first for a discrete cleaning process the input quantity is        determined as a first parameter, the output quantity is        determined as a second parameter, a data processing system        records the determined first and second parameter and stores        them in an ordered manner with reference to one another in the        database as a single dataset for a discrete cleaning process,    -   and then the systematic dependence between the first and second        parameters is systematically derived from a plurality of data        sets, in particular using a plurality of data sets from a        dependency table by means of an algorithm.

It goes without saying that the first part of the procedure, in whichthe first and second parameters are recorded, must first be carried outseveral times in order to obtain a larger number of data sets for thederivation of the systematic dependence, unless existing data can beused.

The corresponding data sets can be collected directly during cleaningprocesses carried out on the vehicle, especially during normal vehicleoperation.

Furthermore, such data sets can also be determined and/or derived fromexperiments in the laboratory.

In a further variant it is conceivable that a data set is determined bymeans of a numerical model, which represents a correspondingpurification process.

In particular, such data sets are stored in a dependency table and thuscollected in the form of empirical values.

From these empirical values, the systematic dependence proposed here canbe derived with the method proposed here. This systematic dependence canthen be used to select or determine the optimal or resource-savingcleaning process.

Preferably the systematic dependence is determined on the basis of atleast 2 data sets, preferably on the basis of at least 50 data sets,further preferred on the basis of at least 200 data sets and especiallypreferred on the basis of at least 1000 data sets.

It should be pointed out that the above values for the number of datasets should not be understood as sharp limits, but rather should be ableto be exceeded or fallen below on an engineering scale without leavingthe described aspect of the invention. In simple terms, the values areintended to provide an indication of the size of the number of data setsproposed here.

By means of the systematic dependence gained in this way, it isadvantageously possible that not only the cleaning processes alreadycarried out can be evaluated and reproduced, but also new cleaningprocesses can be devised on the basis of a systematic analysis of thedata, whereby, among other things, the objective of further reducingresource requirements can be pursued. This can be achieved byinterpolation between the available data sets. Furthermore, it isconceivable that a curve will be generated from the data sets obtained,in particular with a regression method, which enables a continuous anddifferentiable systematic relationship between the input quantities andthe output quantities of the cleaning process.

Preferably, the input quantity is determined by means of at least onesensor.

Optionally, the output quantity is determined by means of at least onesensor.

Expediently, the data processing system exhibits an electronic dataprocessing and evaluation system and a database.

If necessary, it is suggested that the data processing systemdigitalizes the determined first and second parameters, so that therecorded values, in particular the values determined by a sensor, can bemanaged in a digital database and processed electronically.

The systematic dependence between an input quantity and an outputquantity, preferably a resource requirement, developed according to theproposed procedure, describes the system behaviour of the cleaningsystem.

Thus it is concretely conceivable that for each surface to be cleaned arespective systematic dependence is derived which takes into account thepart of the control quantity which is in an effective connection withthe corresponding surface, and whereby the systematic dependencedescribes the cleaning success as well as the resource requirement as afunction of this part of the control quantity as well as possibly alsoas a function of the process quantity, preferably by means of acontinuous and differentiable systematically determined curve, whichreflects the interdependencies of the quantities.

In other words, for a plurality of surfaces to be cleaned, a pluralityof systematic dependencies can be derived, in particular the number ofsurfaces to be cleaned on a vehicle corresponds to the number of derivedsystematic dependencies.

Optionally, a systematic dependence can be in the form of an(n+i)-dimensional curve of m-th order, taking account for ann-dimensional input quantity and an i-dimensional output quantity.

Such systematic dependence can be used in many ways. Thus it isconceivable, among other things, that a comparison of the input quantitycould be used to find the control quantity with which the surface inquestion can be cleaned particularly efficiently in terms of resources.Furthermore, it could be specifically considered that in the comparisonof the ratios of cleaning success and resource requirements, the controlquantity is sought with which a special resource-saving cleaning of thecorresponding surface is possible.

Preferably, the input quantity exhibits the amount of cleaning fluidused to clean the surface to be cleaned.

Preferably, the input quantity exhibits the time period in which thecleaning fluid is applied to the surface to be cleaned.

Preferably, the input quantity exhibits a cleaning means, especially awiping element, with which the surface to be cleaned is treated.

Preferably, the input quantity exhibits the time in which the cleaningmeans is used.

Preferably, the input quantity exhibits the type of the motor vehicleconsidered for the systematic dependence.

Preferably, the input quantity exhibits a quantity of cleaning fluidwith which the surface to be cleaned is soaked before the surface to becleaned is later processed with a cleaning means. Further preferably,the input quantity also exhibits the time during which the surface to becleaned is soaked until it is later processed with the cleaning means.

Preferably, the input quantity exhibits the amount of cleaning fluidused to clean the surface to be cleaned and/or the time period in whichthe cleaning fluid is applied to the surface to be cleaned and/or acleaning means, especially a wiping element, with which the surface tobe cleaned is treated and/or the time in which the cleaning means isused and/or the type of the motor vehicle considered for the systematicdependence and/or a quantity of cleaning fluid with which the surface tobe cleaned is soaked before the surface to be cleaned is later processedwith a cleaning means and/or the time during which the surface to becleaned is soaked until it is later processed with the cleaning means.

The continuous specification of the systematic dependence results in anadvantageous design of the procedure and the possibility to check therobustness of the systematic dependence. Thus, it can be quantifiedwhether the systematic dependence is a regularity or a tendency withcertain probabilities that can be grasped by the continuous precision.

Another advantage of the procedure described here is that an almostunlimited number of parameters can be stored with reference to eachother and used to derive a systematic dependence, preferably an(n+i)-dimensional systematic dependence.

An operator of an appropriate cleaning system is naturally limited inhis ability to map an (n+i)-dimensional systematic dependence, inparticular for the decision regarding the specification of a controlquantity within his brain. In particular by the constantly increasingcomplexity of corresponding cleaning systems and by the increasingnumber of detectable influencing quantities an operator nowadays oftenalready reaches the limits of his natural limitation of hiscomprehension ability. A systematic dependence is not subject to such alimitation and thus advantageous.

According to that, with a suitable implementation of the proposedprocedure, complex correlations between the parameters of the procedurecan be mapped. This applies in particular to dependencies with a largenumber of related quantities, which can show various correlations toeach other.

Advantageously, the aspect of the invention presented here can achievethat the system behaviour of a cleaning system with all its relevantinterdependencies can be mapped, so that a wealth of experience aboutthe proper and resource efficient cleaning of a surface of a vehicletype is created.

In particular, it can be recorded or derived with which resourceefficient cleaning a single surface of a vehicle type can be cleanedefficiently under given environmental conditions and a given initialcontamination of the respective surface.

It should be expressly pointed out that the result of a cleaning processdoes not have to be the complete cleaning of a surface. In particular,it should be specifically considered that the cleaning success of asurface is only so small that it remains functional for the sensorhidden behind it.

This applies in particular to the front and rear windows of a motorvehicle, which after completion of a cleaning process are cleaned atleast to such an extent that the sensor behind the windscreen,preferably the driver of the motor vehicle in the interior of the same,can operate through the front and rear windows in such a way that safedriving operation does not fail due to soiling of the front and/or rearwindows.

In this way, cleaning resources can be advantageously saved by using acleaning method that makes use of such systematic dependence, whereby afurther distance can be safely driven by the motor vehicle with the sameinitial conditions on existing cleaning resources and/or whereby themotor vehicle weight can be reduced, since fewer resources have to beused for the same distance to be covered and/or whereby the associatedfluid tank of the motor vehicle can be designed smaller for a cleaningfluid, whereby installation space within the motor vehicle can be saved.

Expediently, the input quantity exhibits at least one measured quantity,preferably a process quantity and/or a control quantity.

It is suggested here that the input quantity exhibits a measuredquantity.

If the input quantity lacks exhibiting a measured quantity, a systematicdependence could conceivably also be dependent on default values of thecontrol quantity within the framework of a control system.

But, by using a measured quantity, the accuracy of the systematicdependence can be advantageously increased.

Preferably such a measured quantity is a control quantity, so that asystematic dependence between the output quantity and the controlquantity of a cleaning process of a surface of a motor vehicle to becleaned can be derived and thus later also be used for the cleaning ofthe corresponding surface, in particular for the control and/orregulation of a cleaning process for the surface to be cleaned.

Furthermore, it is suggested that the input quantity exhibits a processquantity, so that a systematic relationship between the output quantityand the process quantity, preferably the air humidity and/or the airtemperature and/or the actual solar radiation and/or the temperature ofthe surface to be cleaned, can be derived during a cleaning process of asurface of a motor vehicle to be cleaned and thus later also be used forthe optimal cleaning of the corresponding surface.

The advantage of this is that the accuracy of a derived systematicdependence can be increased and at the same time a multitude ofinfluencing factors from the area of control quantity and/or processquantity can be taken into account.

Preferably, the input quantity exhibits a driving speed of the motorvehicle.

The driving speed of a motor vehicle may influence a cleaning process ofa surface to be cleaned, in particular the distribution of a cleaningfluid on the surface to be cleaned and/or the displacement of a cleaningfluid on the surface to be cleaned by the relative airstream and/orevaporation of a cleaning fluid on the surface to be cleaned, wherebythe effective exposure time in which a cleaning fluid may dissolvecontaminants may also be influenced.

If the input quantity contains the driving speed, the influence of thedriving speed can also be taken into account for the optimal cleaning ofthe surface to be cleaned using the systematic dependence derived here.

In a preferred embodiment, the input quantity exhibits a humidity, inparticular a current humidity in the vicinity of the motor vehicle,and/or a temperature in the vicinity of the motor vehicle, in particulara current temperature in the vicinity of the motor vehicle and/or arainfall quantity, in particular a current rainfall quantity in thevicinity of the motor vehicle, and/or a snowfall quantity, in particulara current snowfall quantity in the vicinity of the motor vehicle, and/ora coordinate of the motor vehicle.

It has been shown that air humidity and air temperature are importantfactors influencing the cleaning success of a cleaning process on asurface to be cleaned.

For this reason, it is proposed here that the systematic dependence onthese particularly relevant influencing factors for a resource efficientcleaning is derived.

It has also been shown that rain and/or snow can make the cleaningprocess more resource-efficient. In particular, rain and/or snow cancause deposited dirt to become detached or at least softened and thuseasier to dissolve, thus saving cleaning fluid.

Provided that the effective temperature and/or the effective humidityand/or the effective amount of rain and/or the effective amount of snoware taken into account when deriving the systematic dependence, thesedata can also be taken into account when evaluating a purificationprocess.

In particular, it is conceivable that the current environmentalconditions are also taken into account when selecting a cleaningprocess, in particular specified by a control quantity setpoint, so thatan optimally resource-saving and/or resource-efficient cleaning processcan be selected and carried out.

Furthermore, it is conceivable that the current coordinate of thevehicle is also taken into account, especially when statisticallyconsidering an expected temperature and/or an expected humidity and/oran expected amount of rain and/or an expected amount of snow. Thus it isconcretely conceivable that the expected environmental conditions aredetermined on the basis of the current coordinate of the vehicle andthat an optimal resource-saving and/or resource-efficient cleaningprocess is selected on the basis of the expected environmentalconditions and the systematic dependence and implemented for thecleaning of a surface to be cleaned.

The advantage of this is that important influencing factors can besystematically taken into account when cleaning a surface to be cleanedand can thus also be taken into account in the resource efficientcleaning, preferably resource-saving cleaning, of a surface in thefuture, saving resources and increasing the operational safety of themotor vehicle.

In an optional embodiment, the input quantity exhibits a vehicle type.

The vehicle type provides information about a large number of differentinfluencing factors that affect the cleaning process of a part of thesurface of a motor vehicle. These include, among others, the position atwhich a surface to be cleaned is installed and/or the size of a surfaceto be cleaned and/or the cleaning means with which the surface to becleaned can be cleaned and/or the degree of contamination to be expectedand/or the type of contamination to be expected and/or the exposure ofthe surface to be cleaned to the airstream and/or the exposure of thesurface to be cleaned to the sunlight and/or the number of surfaces tobe cleaned.

Furthermore, the vehicle type provides information about the respectiveinstalled function type of a sensor and/or a respective installed sensortype, in particular about all different function types of sensors and/orsensor types located on the motor vehicle, including an assignment tothe location where the respective sensor is installed.

It is proposed here to consider these influencing factors when derivingthe systematic dependence.

The advantage of this is that influencing factors associated with thevehicle type can be taken into account for the systematic dependence andcan therefore also be applied individually for each vehicle type in thefuture in the interest of resource efficient cleaning.

Expediently, the input quantity exhibits an availability of the sensor.

The availability of a sensor is a quantity that can ultimately provideinformation about how heavily a sensor is soiled.

Particularly preferred, availability can assume values in an interval,whereby one interval limit on reaching means that the system can fullyfulfill its requirements, and the other interval limit on reaching meansthat the system can no longer fulfill its requirements.

If the availability value ranges between the interval limits, the systemcan still fulfill its requirements, but under more difficult conditions.In particular, the value of availability reflects the degree ofcontamination of the surface of the motor vehicle, preferably the degreeof contamination of the surface, preferably the surface of a sensor,particularly preferably the degree of soiling of the surface of anoptical sensor and/or the degree of soiling of a window through whichthe driver of the motor vehicle looks, in particular the degree ofsoiling of the windscreen and/or the rear window, and/or the degree ofsoiling of a headlamp and/or a rear-headlamp.

It turned out that the availability of a sensor before the cleaningprocess of a surface has an influence on the cleaning success with thesame control quantity but different availabilities before the cleaningprocess.

It can be advantageously achieved by the aspect proposed here that theavailability of the sensor can be taken into account as an influencingfactor for the derived systematic dependence.

Preferably, the output quantity exhibits an availability of the sensorand or a gain in availability due to the cleaning process.

The aspect of the invention proposed here makes it possible to determinethe cleaning success of a cleaning process, in particular by comparingthe availability of the sensor before and after the cleaning process,which is called the gain in availability.

In other words, gain in availability is the difference between theavailability immediately after completion of the cleaning process andthe availability immediately before the cleaning process.

Thus, the success of the cleaning process, preferably the gain inavailability, can be quantified advantageously by the aspect proposedhere.

This enables for future cleaning processes in an advantageous way, thatthe control quantity can be determined by means of the systematicdependence on the availability of the sensor prior to the cleaningprocess with which on the one hand a resource efficient cleaning of thesurface to be cleaned can be carried out and on the other hand a desiredavailability of the sensor after the cleaning process can be achieved.

It should also be specifically considered that a selected cleaningprocess, which is specified by the selection of the control quantity,does not necessarily clean the availability of the sensor up to theupper limit of the determinability of the availability of the sensor,but only as far as it is necessary under a function-relevant and/orsafety-relevant aspect.

Furthermore, it is conceivable that a number of cleaning processes,specified by their respective control quantity, can be carried out oneafter the other in order to achieve optimum cleaning in terms ofresource efficiency and/or the functionality of the sensor and/or asafety aspect for the motor vehicle.

It should be specifically considered that such a sequence of cleaningsteps is already defined before the first cleaning process.

Furthermore, it is conceivable that between the cleaning processes of acleaning sequence for a surface, the availability of the respectivesensor will be re-evaluated and that the control quantity for thesubsequent cleaning process will be determined depending on theavailability of the respective sensor achieved in the meantime.

Overall, it can be advantageously achieved that the cleaning of one ormore surfaces of a motor vehicle can run autonomously or at leastpartially autonomously.

In an expedient embodiment, the output quantity exhibits a resourcerequirement of the cleaning process of the surface of the motor vehicle,preferably the resource requirement is determined depending on a controlquantity setpoint for the cleaning process of the surface.

This can be advantageous in that the resource requirements of a cleaningprocess can be taken into account when using the systematic dependence,among others when selecting the optimum cleaning process represented bya control quantity setpoint for the current initial condition from whicha cleaning of a surface to be cleaned is to be optimized.

In a preferred embodiment, the systematic dependence is determined bymeans of a regression analysis.

Here it is suggested to use a regression algorithm as algorithm for theindirect derivation of a systematic dependence.

An algorithm which has already been tested in a large number ofapplications and which can be optimally selected and/or adaptedaccording to the system behaviour considered here can thus beadvantageously applied so that a systematic dependence of high qualitycan be determined.

Expediently, the systematic dependence is determined in form of a curve,preferably a curve and a coefficient of determination of the curve.

The advantage of this is that the systematic dependence is indicated bya curve as a function of an input quantity of the cleaning process; inparticular, this curve has no gaps, so that a clear assignment between acontrol quantity and an output quantity can be achieved, in particular acontinuous and differentiable dependency between an input quantity andan output quantity, so that the dependency is ideally adapted for anoptimization, in particular an optimization of the resource requirement.

Preferably, a curve is continuous and differentiable, so that it can beadvantageously achieved that by using the systematic dependence in thecontrol range of a control quantity, a control quantity suitable for therequirements of a cleaning process can be determined, without thisleading to discontinuities in the adjustment range or to anundifferentiable change in the influence of a variation of a controlquantity.

The evaluation of a coefficient of determination from the determineddata and the curve determined by means of a regression model provides anindication for the precision of the systematic dependence, assuming thata sufficient number of data sets is available. It can be advantageouslyevaluated how meaningful a correlation between an input quantity of thecleaning process and an output quantity is and how well existing orrecorded data can be reproduced. In addition, in the case of a largecoefficient of determination, the curve also allows statements to bemade about the margins of existing data. It is conceivable, for example,that data can be supplemented numerically and/or extrapolated at themargins of existing data.

In an optional embodiment, the systematic dependence is determined bymeans of an optimization process.

Here it is suggested that the parameters of a systematic dependence aredetermined by means of an optimization procedure, especially by means ofa minimization procedure, which minimizes the cumulated deviation of theempirical values considered by data sets from the systematic dependence.In this way, it is advantageously possible to determine a systematicdependence which can be derived in an optimal way, in particular with aminimum cumulated deviation from the initial experience values.

Preferably, the parameters of the systematic dependence are determinedby maximizing the resulting coefficient of determination.

Preferably, the systematic dependence is determined by means of aself-learning optimization method.

Among other things, it is proposed to use an algorithm that exhibits thecharacteristics of an algorithm from the class of machine learning.Thus, the algorithm is able to derive a systematic dependence betweenthe input quantity and the output quantity.

The advantage of this is that the complex task of indirectly deriving asystematic dependence by using self-learning optimization methods doesnot have to be laboriously adapted by humans to new conditions. Thus,time and money can be saved in the indirect derivation of systematicdependence.

The quality of the derived systematic dependence can be improved by theaspect proposed here, since an optimization procedure endeavors todetermine the optimal systematic dependence even in a multi-criteriaenvironment and under a variety of boundary conditions.

In this way, it is also conceivable that an optimization can be carriedout under a plurality of equal objectives and/or boundary conditions(multi criteria optimization). In particular, a plurality of requiredresources can be minimized while simultaneously maximizing a gain inavailability. In particular, a class of algorithms is considered whichcan determine a Paretooptimum and/or a Paretofront. In particular, aclass of algorithms in the area of simplex methods and/or evolutionarystrategies and/or evolutionary optimization algorithms and/or the likeare suggested here for deriving a systematic dependence.

Expediently, the systematic dependence is derived using data sets froman already existing database.

The advantage of this is that data from an existing database can also beused to derive a systematic dependence. Thus, it can be achieved thatempirical values do not have to be collected at a specific motor vehiclefirst and transferred into data of a database and later into asystematic dependence. In this way, existing data and empirical valuescan be used to ensure direct operation of the cleaning system of a motorvehicle on the basis of the systematic dependence.

In an optional embodiment, the already existing database is continuouslyexpanded.

Advantageously, it can be achieved that the number of derivablesystematic dependencies increases over time.

Furthermore, it can be advantageously achieved that the accuracy of asystematic dependence can increase due to the larger number of empiricalvalues known by means of data sets.

In an expedient embodiment, a new data set replaces the data set whichdeviates most from the derived systematic dependence.

In particular, the fact that the experience value is exchanged with thelargest Euclidean distance to systematic dependence should be taken intoaccount.

Advantageously, it can be achieved that the systematic dependencebecomes more and more precise over time, which can be expressed by anincrease in the coefficient of determination.

Furthermore, this can have the advantage that even weakly correlatingsystematic dependencies can be better identified over time.

It should be noted that the subject-matter of the second aspect can beadvantageously combined with the subject-matter of the first aspect ofthe invention, either individually or cumulatively in any combination.

According to a first alternative of a third aspect of the invention, thetask is solved by a method for optimizing a resource requirement for acleaning process of a surface of a motor vehicle, whereby a sensor isoperatively connected to the surface, whereby the method uses data froma dependency table for a system behaviour of a cleaning system of themotor vehicle, preferably for a system behaviour of a cleaning processof at least one surface, preferably a resource efficient cleaning,particularly preferably a resource-saving cleaning, whereby thedependency table exhibits data sets each exhibiting an input quantity ofthe cleaning system and an output quantity of the cleaning system,whereby the output quantity depends on the input quantity by means ofthe system behaviour of the system, preferably the dependency table forthe system behaviour of the cleaning system between at least one controlquantity of the cleaning process, an availability of the sensor at astart time of the cleaning process and an availability of the sensor atan end time of the cleaning process, wherein the resource requirement ofthe cleaning process depends on the control quantity, exhibiting thefollowing steps:

-   -   Access the data of the dependency table from a database and/or        an electronic data processing and evaluation unit and/or an        electronic control unit;    -   Derive a difference between the availability of the sensor at an        end time of the cleaning process and the availability of the        sensor at a start time of the cleaning process for each data set        of the dependency table;    -   Derive a ratio of that difference to the respective resource        requirement for each data set of the dependency table;    -   Select the control quantity of the data set exhibiting the        highest value of that ratio; and    -   Preferably store that control quantity as a control quantity        setpoint in the database and/or the electronic data processing        and evaluation unit and/or the electronic control unit.

The increasing number of vehicle assistance systems requires anincreasing number of sensors installed in an engine vehicle. Since thesesensors mainly detect an optical signal, they are dependent on the factthat the surface through which the optical signal is detected, which isoperatively connected to the sensor, is sufficiently clean. The degreeof cleanliness is individually defined by the individual sensor by thefact that it can receive and/or process the respective optical signal tobe processed at least predominantly interference-free.

Thus, the surface in an active connection with the sensor must becleaned from time to time by the use of cleaning means. This alsoapplies to the majority of sensors that do not operate with an opticalsignal, as the signal transmission of these sensors can also be impairedby contamination.

It should therefore be expressly pointed out that this aspect of theinvention can affect not only optical sensors but all sensors on a motorvehicle, at least those which are in an active connection to a surfaceof the motor vehicle.

Each cleaning process is linked to a resource requirement, which must beprovided by the motor vehicle.

So far it is known that a cleaning process is initiated manually,preferably by the driver of the motor vehicle.

The increasing number of vehicle assistance systems and thus also theincreasing number of sensors installed in a motor vehicle has recentlyincreased, which is why the need for resources to be kept available hasalso increased significantly.

Due to the increase in sensors, the control effort for the necessarynumber of cleaning processes has also increased, which is whysemi-automated or automated cleaning of the relevant surfaces is alsodesirable.

An advantageously automatable procedure for minimizing the consumptionof resources for the cleaning of surfaces that are effectively connectedto the relevant sensors is now proposed, in particular by carrying outeach individual cleaning process preferably resource-efficient,especially resource-saving, so that the consumption of resources andthus also the resource requirement of at least one cleaning means can bereduced advantageously.

Each cleaning process is defined by at least one parameter, inparticular an input quantity, particularly preferably by a controlquantity. The amount of cleaning fluid applied to a surface to becleaned could be considered as a respective input quantity or at thesame time a respective control quantity.

Preference should also be given to the fact that a cleaning liquid isapplied in several phases to a surface to be cleaned, preferably in afirst phase a comparatively small quantity by means of which anycontamination can be softened and in a second phase a second quantity bymeans of which the softened contamination can be washed off the surface.The way in which a cleaning agent is used, in particular the amount ofcleaning fluid, has a direct influence on the resource requirements fora single cleaning process.

It should be noted that this aspect considers not only the amount ofcleaning fluid required for a cleaning process, but also the amount ofenergy used for cleaning, the wear of wiping elements and/or comparableresources required for a cleaning process.

Each cleaning process is subject to a system behaviour, whereby thesystem behaviour depends on at least one parameter, preferably an inputquantity, particularly preferably a control quantity, and within theframework of an output quantity also enables a statement to be madeabout the result of a cleaning process, in particular about the resourcerequirement used or to be used in the sense of a planning as well asabout the cleaning success, particularly preferably by means of anavailability.

Thus, a system behaviour is preferably defined by at least one inputquantity and at least one output quantity, whereby the at least oneoutput quantity depends on the at least one input quantity.

In the case of an input quantity, the size of the surface that isoperatively connected to a sensor and therefore to be cleaned could alsobe considered.

Preference could also be given to the position of a surface to becleaned in the context of an input quantity. Thus a difference for aresource efficient, especially preferred resource-saving, cleaningmethod can result from whether a surface to be cleaned can be found atthe front or at one side or at the back or at the bottom or at the topof a motor vehicle.

Furthermore, an input quantity could also include a type ofcontamination, in particular whether it is an encrusted deposit of dirtand/or dust or a layer of sludge or snow or the like. It should also beborne in mind that the operating location and operating history of amotor vehicle allow a statistical expectation for the type ofcontamination of a surface, especially in combination with the weatherreport. In other words, the scope of an input quantity could alsoinclude the weather conditions as well as an operating location and/oran operating history, which can be evaluated by a coordinate of themotor vehicle and, if necessary, other retrievable data, in particulardata retrievable from a data network.

When evaluating the cleaning success of a cleaning process, it couldpreferably be remembered that the success is thought of as thedifference between the availability of the corresponding surface to becleaned before and after the cleaning process.

Differently defined cleaning processes can be evaluated on the basis oftheir system behaviour consisting of at least one input quantity and atleast one output quantity.

If there are empirical values for a number of defined cleaningprocesses, a resource efficient, particularly preferred resource-saving,cleaning can be selected specifically on the basis of the existingempirical values for the respective contamination situation.

A respective empirical value consists of at least one input quantity, inparticular a control quantity, and at least one output quantity, inparticular a gain in availability, determinable from the differencebetween the availability before cleaning and after cleaning the surfaceto be cleaned.

In this context, it could be specifically considered that the controlquantity which has produced an optimal resource efficient, especiallypreferred resource-saving, cleaning according to the existing experienceis selected on the basis of the existing contamination situation, inparticular the available availability, and that the correspondingcontrol quantity is reproduced within the framework of a cleaningprocedure. During the reproduction, a control quantity or a controlledcleaning process can be considered in particular.

Possible empirical values can preferably consist of experience gained ona motor vehicle, in particular the specific motor vehicle, and/or ofempirical values from experience gained on reference vehicles and/orexperience generated on the basis of a numerical model and/or experiencegenerated on the basis of laboratory tests.

The empirical values taken into consideration for the selection of aresource-efficient, particularly resource-saving, cleaning processpreferably relate to the respective experiences gained on the basis ofthe surface to be cleaned which is now also to be cleaned or at leastthe cleaning of which is now to be evaluated.

When storing collected empirical values, the data could be stored in adependency table.

Preferably a dependency table can be extended by new empirical values.

A dependency table can be read out preferentially.

Preferably a dependency table can be stored in a database and/or anelectronic data processing and evaluation unit and/or an electroniccontrol unit.

Preferably a dependency table shows the possibility to storeintermediate results for the evaluation of a cleaning process in anorderly way.

Preferably a dependency table allows the selection of a concreteexperience value by means of data mining methods known in the state ofthe art.

In other words, it is suggested here that the resource consumption forthe cleaning of a surface selected for cleaning is optimised on thebasis of the system behaviour of the cleaning process, so that a bettercleaning result can be achieved advantageously with a lower resourceinput, in particular depending on the current initial situation.

The optimal control quantity setpoint corresponds to the controlquantity of the experience value for a defined cleaning process thatpromises the resource-optimal cleaning of the surface to be cleanedaccording to the proposed procedure. If a corresponding optimumexperience value has been selected, the optimum control quantitysetpoint can be taken from the corresponding input quantity.

The method proposed here is designed to optimize the cleaning of asurface that is interrelated with a sensor and produces a controlquantity setpoint optimized for the individual surface to be cleaned.

Preferably, the procedure can be performed sequentially for a number ofsurfaces to be cleaned, which is advantageous in that a control quantitysetpoint can be defined sequentially for each surface of the motorvehicle to be cleaned.

This could be achieved by the following steps:

-   -   Access the data of the dependency table from a database and/or        an electronic data processing and evaluation unit and/or an        electronic control unit, whereby the collected expected values        can be called advantageously and processed in the next step;    -   Derive a difference between the availability of the sensor at an        end time of the cleaning process and the availability of the        sensor at a start time of the cleaning process for each data set        of the dependency table, which advantageously determines a gain        in availability for each stored experience value;    -   Derive a ratio of that difference to the respective resource        requirement for each data set of the dependency table, whereby        an efficiency of a cleaning process can be advantageously        defined by the ratio of expected resource requirements and        expected cleaning success;    -   Select the control quantity of the data set exhibiting the        highest value of that ratio, whereby the most resource-efficient        control quantity can be selected on the basis of existing        empirical values; and    -   Preferably store that control quantity as a control quantity        setpoint in the database and/or the electronic data processing        and evaluation unit and/or the electronic control unit, so that        the specific control quantity setpoint can be retrieved and        applied advantageously within the framework of a downstream        cleaning process.

According to a second alternative of a third aspect of the invention,the task is solved by a method for optimizing a resource requirement fora cleaning process of a surface of a motor vehicle, wherein a sensor isoperatively connected to the surface, whereby the method uses asystematic dependence for a system behaviour of a cleaning system of themotor vehicle, preferably a systematic dependence according to thesecond aspect of the invention, preferably for a system behaviour of acleaning process of at least one surface, preferably a resourceefficient cleaning, particularly preferably a resource-saving cleaning,whereby the systematic dependence exhibits data sets each exhibiting aninput quantity of the cleaning system and an output quantity of thecleaning system, whereby the output quantity depends on the inputquantity by means of the system behaviour of the system, preferably thesystematic dependence for the system behaviour of the cleaning systembetween at least one control quantity of the cleaning process, anavailability of the sensor at a start time of the cleaning process andan availability of the sensor at an end time of the cleaning process,wherein the resource requirement of the cleaning process depends on thecontrol quantity,

exhibiting the following steps:

-   -   Access the systematic dependence from a database and/or an        electronic data processing and evaluation unit and/or an        electronic control unit;    -   Derive a course of a difference between the availability of the        sensor at an end time of the cleaning process and the        availability of the sensor at a start time of the cleaning        process for a course of the systematic dependence;    -   Derive a course of a ratio of that course of difference to a        course of the respective resource requirement for the course of        the systematic dependence;    -   Select the control quantity which belongs to the point in the        course of that ratio exhibiting the highest value of that ratio;        and    -   Preferably store that control quantity as a control quantity        setpoint in the database and/or the electronic data processing        and evaluation unit and/or the electronic control unit.

According to the above first alternative of the third aspect of theinvention, discrete empirical values are used for the procedure foroptimizing a resource requirement for a cleaning process, preferably fora resource efficient cleaning, particularly preferably a resource-savingcleaning.

The resolution of an input quantity, in particular a control quantity,in the range of the possible expression of an input quantity depends onthe number of usable empirical values and the distribution of theseusable empirical values in the range of the possible expression of theinput quantity.

In a different way, it is proposed here to map the system behaviour of acleaning process by means of a systematic dependence, preferably bymeans of a systematic dependence according to the second aspect of theinvention.

Preferably a systematic dependence exhibits data sets, where each dataset exhibits an input quantity of the cleaning process and an outputquantity of the cleaning process. Among other things, it is conceivablethat a systematic dependence is represented by a defined number of datasets and a defined distribution in the range of the possible inputquantity.

This allows advantageously that the data sets of the systematicdependence were derived from empirical values in such a way that in thesense of the objective of a resource efficient cleaning, particularlypreferably a resource-saving cleaning, an optimal number of data setsand an optimized distribution of the data sets resulted in the range ofthe possible expression of the input quantity.

As far as it concerns concrete data sets in the context of systematicdependence, which are defined by input quantity and output quantity,these can be proceeded preferentially also according to the proceduralsteps after the first alternative of the third aspect.

Alternatively, it is also conceivable that a systematic dependence isgiven by its mathematical description. In this case the systematicdependence consists of a curve, which describes the dependence betweenthe at least one input quantity and the at least one output quantity.

Particularly preferably, a systematic dependence in the form of a curveover the complete definition range of the curve describes a dependenceof at least one output quantity of at least one input quantity.

The preferred definition range of the curve is at least as large as therange of the possible expression of the input quantity.

Also in the case where a systematic dependence is defined by a curve, itcan be said that the systematic dependence exhibits data sets eachexhibiting at least one input quantity of the cleaning system and atleast one output quantity of the cleaning system. In particular, becauseindividual data sets can be read from its curve, for example bycalculating an output quantity for a grid of an input quantity.

Preferably the systematic dependence has at least one control quantityas input quantity.

Preferably the systematic dependence has a dependency between anavailability of the sensor at a start time of the cleaning process andan availability of the sensor at an end time of the cleaning process,which allows a gain in availability to be determined.

It can be advantageously achieved by using a systematic dependence thata mathematical method can be used to determine an extreme value of thesystem behavior when searching for an optimal control quantity,especially if the systematic dependence is continuous and differentiablein the form of a curve.

Further it can be reached by this alternative advantageously that in thecomparison to the first alternative of the third aspect of the inventiona better optimum can be determined for the control quantity setpoint, sothat in the comparison advantageously still more resource savings can bemade possible.

This is on the one hand due to the fact that by the process of thedetermination of the systematic dependence, in particular thedetermination after the second aspect of the invention, measurementinaccuracies and fluctuations in the system behavior can be smoothed,whereby preferably from a discrete description by means of discreteempirical values a continuous thus steady and differentiablerepresentation of the systematic dependence is produced, whereby agreater degree of accuracy of the mapping of the system behaviour can beachieved.

Furthermore, the optimization result can be improved by selecting anoptimal control quantity setpoint also from those areas which areoptimal from a mathematical point of view but for which there arecurrently no empirical values available.

Here it is concretely proposed that the resource consumption for thecleaning of a surface selected for cleaning is optimised on the basis ofthe system behaviour of the cleaning process, so that a better cleaningresult can be achieved advantageously with a lower resource input, inparticular depending on the current initial situation and using asystematic dependence according to the second aspect of the invention.

The method proposed here is designed to optimize the cleaning of asurface that is interrelated with a sensor and produces a controlquantity setpoint optimized for the individual surface to be cleaned.

Preferably, the procedure can be performed sequentially for a number ofsurfaces to be cleaned, which is advantageous in that a control quantitysetpoint can be defined sequentially for each surface of the motorvehicle to be cleaned.

It is understood that the procedural steps following the secondalternative of the third aspect should be slightly modified from thefirst alternative of the third aspect:

In particular, a dependency table in a database and/or an electronicdata processing and evaluation unit and/or an electronic control unit isnot accessed, but rather a corresponding systematic dependence, inparticular a systematic dependence according to the second aspect of theinvention.

Furthermore, it is also understood that preferably no discrete datapoints are used for the calculation, but that the respectivemathematical operations are preferably carried out with the entire curveover the entire course of the curve. This can preferably be doneanalytically or in defined steps by means of discretization.

In addition, it is understood that the advantages of systematicdependence are exploited and the data set is not selected from thedocumented empirical values, which promises the optimal resource-savingcleaning of the surface to be cleaned, but instead the extreme point inthe course of the systematic dependence, at least the extreme point inthe area in which the control quantity can be adapted. In particular, itis understood that the selected control quantity setpoint can be locatedat the edge of the range by adjusting the control quantity.

It should be expressly pointed out that the systematic dependenceconsidered here is not limited in its dimensionality and can have anynumber of dimensions of an input quantity and any number of dimensionsof an output quantity.

Preferably,

-   -   the dependency table and/or the systematic dependence exhibits a        dependency to a process quantity, preferably a humidity and/or a        temperature in the vicinity of the motor vehicle and/or a        rainfall and/or a snowfall quantity and/or a coordinate of the        motor vehicle; and    -   wherein, prior to the selection of the control quantity, the        data sets taken into account in the selection of the control        quantity from the dependency table and/or the area of the        systematic dependence taken into account in the selection of the        control quantity are first restricted to an area which deviates        from the respective process quantity, preferably a current        humidity and/or a forecast humidity along the planned itinerary        and/or a current temperature in the vicinity of the motor        vehicle and/or a forecast temperature along the planned        itinerary and/or a current rainfall and/or a forecast rainfall        along the planned itinerary and/or a current snowfall quantity        and/or a forecast snowfall quantity along the planned itinerary        and/or a coordinate of the motor vehicle and/or a forecast        coordinate of the motor vehicle along the planned itinerary, by        less than 20%, preferably deviates by less than 10% and        particularly preferably deviates by less than 5%.

Here it is specifically proposed that the optimization of the controlquantity setpoint, in other words the minimization of the resourcerequirement for cleaning a single surface of a motor vehicle to becleaned, also takes at least one process quantity into account.

It goes without saying that the cleaning success of a cleaning processcarried out after a long period of drizzle is different than if thecleaning process defined by the identical control quantity is carriedout on a hot summer day with intense sunshine, at least taking intoaccount the same previous degree of soiling and the same type ofsoiling.

In other words, a resource-optimal cleaning process also depends on atleast one process quantity, which is why it could be taken into accountwhen optimizing the optimal control quantity setpoint.

The same can be achieved if the empirical values stored in a dependencytable are initially dependent on the process quantity, preferably theprocess quantity concerned. The same applies when using a systematicdependence, in particular a systematic dependence after the secondaspect of the invention, which must also have a dependency on theprocess quantity, preferably the process quantity concerned, so thatwhat is suggested here can be taken into account accordingly in theoptimization.

For consideration within the optimization it is proposed that the numberof experience values from the dependency table taken into account whenselecting the optimal control quantity setpoint and/or the range ofsystematic dependence be limited to a range which does not deviate bymore than 20% from the currently prevailing process quantity or theprocess quantity expected according to the weather forecast at the timeof the planned cleaning process, preferably deviates by less than 10%and particularly preferably deviates by less than 5%.

By this way of limitation it can be achieved that no experiences from acleaning process made in sunshine are transferred to a pending cleaningin snowfall. In other words, it can be achieved that only experiencesfrom a situation which essentially corresponds to the impending cleaningsituation are transferred to the respective situation.

Among other things, the mapping accuracy between the selected controlquantity expected to be optimal and the result achieved during thecleaning process can be advantageously improved.

A process quantity is preferably understood as the weather on thepre-planned route. The decision on an optimal control quantity setpointcould also depend on whether weather conditions are reached on thepreplanned route that require less resources for cleaning, in particularrain and/or snowfall. In this way, it can be advantageously achievedthat the total resources required for cleaning can be advantageouslyreduced by including the expected weather conditions in the decision onthe control quantity setpoint, which can also include the cleaning time.This is among others also suggested by the inclusion of a processquantity.

It should be pointed out that the above values for the considered areaof the process quantity should not be understood as sharp limits, butrather should be able to be exceeded or fallen below on an engineeringscale without leaving the described aspect of the invention. In simpleterms, the values are intended to provide an indication of the size ofthe considered process quantity regime proposed here.

Expediently,

-   -   the dependency table and/or the systematic dependence exhibits a        dependency to the availability of the sensor at the start time        of the cleaning process; and    -   wherein prior to the selection of the control quantity, the data        sets taken into account in the selection of the control quantity        from the dependency table and/or the area of the systematic        dependence taken into account in the selection of the control        quantity are first restricted to an area which deviates from the        actual availability of the sensor and/or an expected        availability of the sensor at a point on the planned route by        less than 20%, preferably deviates by less than 10% and        particularly preferably deviates by less than 5%,    -   in particular by applying a method for determining an expected        availability at a distance or an operating time of the motor        vehicle yet to be covered, preferably according to the tenth        aspect of the invention.

It is suggested here to include the availability of the sensor in anactive connection with the surface to be cleaned in the optimization ofthe control quantity setpoint.

Measured by a gain in availability, a cleaning process defined by acontrol quantity results in different cleaning successes with differentinitial soiling of the surface. Preferably, better cleaning resultsresult for a more heavily soiled initial situation than for a lessheavily soiled surface, whereby a comparable resource requirement isrequired in each case, since cleaning is carried out with the identicalcontrol quantity in each case.

In this respect, the contamination at the beginning of a cleaningprocess can influence the resource efficiency of a cleaning process.

A consideration of the initial contamination situation of a surface tobe cleaned, in particular evaluated by an availability of the sensor atthe start time of the cleaning process, is made possible by the factthat the empirical values stored in a dependency table first have adependency on the availability of the sensor at the start time of thecleaning process. The same applies when using a systematic dependence,especially a systematic dependence after the second aspect of theinvention, which must also have a dependency on the availability of thesensor at the start time of the cleaning process, so that this can beconsidered accordingly in the optimization.

When considering an availability of the sensor at the start time of thecleaning process, the same applies as has already been done forconsidering a process quantity. Here, too, the range of empirical valuesconsidered for the optimization from a dependency table and/or the rangeof systematic dependence will be limited to a range which deviates fromthe actual availability of the sensor by less than 20%, preferablydeviates by less than 10% and particularly preferably deviates by lessthan 5%.

Due to the resulting limitation, it can be advantageously achieved thatonly experiences from situations that essentially coincide with theforthcoming cleaning situation are transferred to these situations.

Among other things, the mapping accuracy between the selected controlquantity expected to be optimal and the result achieved during thecleaning process can be advantageously improved.

Furthermore, it should be specifically considered here, among otherthings, that in the preliminary planning of an upcoming cleaningprocess, an expected availability of the sensor at the time of carryingout the cleaning process is estimated in advance, in particular with aprocedure according to the tenth aspect of the invention.

Thus, depending on the distance to be covered by the motor vehicle untilthe cleaning process or on the operating time to be covered by the motorvehicle until the cleaning process, an expected availability of thesensor can first be determined, on the basis of which the limitation ofthe empirical values from the dependency table and/or the area ofsystematic dependence can be carried out.

The planning accuracy of a cleaning process can be improvedadvantageously, whereby the resource requirement for the cleaning of asurface connected to a sensor can also be reduced advantageously.

It should be pointed out that the above values for the considered areaof the availability of the sensor at the start time of the cleaningprocess should not be understood as sharp limits, but rather should beable to be exceeded or fallen below on an engineering scale withoutleaving the described aspect of the invention. In simple terms, thevalues are intended to provide an indication of the size of theconsidered availability of the sensor at the start time of the cleaningprocess proposed here.

Optionally,

-   -   the dependency table and/or the systematic dependence exhibits a        dependency to the availability of the sensor at the start time        of the cleaning process;    -   wherein prior to the selection of the control quantity, the data        sets taken into account in the selection of the control quantity        from the dependency table and/or the area of the systematic        dependence taken into account in the selection of the control        quantity are first restricted to an area where the availability        of the sensor at the start time of the cleaning process is less        than or equal to the actual availability of the sensor; and    -   wherein the availability of the sensor at the start time of the        cleaning process associated with the selected control quantity        is additionally saved with the selected control quantity as the        control quantity setpoint.

Contrary to the above, it is now proposed to optimise a cleaning processwith regard to its resource efficiency in such a way that at the time ofoptimisation a decision is also made on the condition which must befulfilled for the cleaning process to be started, in particular on anavailability of the sensor which is to be achieved for the cleaningprocess to be started.

In other words, a pre-planned cleaning process shall be started by acleaning method, in particular by a cleaning method according to thefirst aspect of the invention, if a predetermined availability of thesensor at start time of the cleaning process is achieved by the processproposed here.

The proposed method is made possible by the fact that the empiricalvalues stored in a dependency table first have a dependency on theavailability of the sensor at the start time of the cleaning process.The same applies when using a systematic dependence, especially asystematic dependence after the second aspect of the invention, whichmust also have a dependency on the availability of the sensor at thestart time of the cleaning process, so that this can be consideredaccordingly in the optimization.

At the same time, in addition to the control quantity setpoint, theoptimum availability of the sensor at the start time is also selected ordetermined from the input quantity of the selected optimum empiricalvalue or the optimum point of systematic dependency.

After the sensor, which is in an effective connection with the surfaceto be cleaned, already exhibits an actual availability value, onlyoptimal cleaning processes can be selected by means of this method,which either start immediately because the resource-optimal cleaningprocess within the scope of the physically possible already lies on thecurrently reached limit of availability of the sensor, or start in thefuture with a defined availability of the sensor at start time, sincethis must first be achieved by additional contamination of the surfaceto be cleaned.

By storing the selected control quantity setpoint together with theavailability of the sensor at the start time of the cleaning process,the cleaning method can start the cleaning process by reaching thedetermined optimal availability of the sensor at the start time of thecleaning process.

The resource requirement of the cleaning process can thus be furtherreduced in an advantageous way, since the procedure proposed hereselects the cleaning process that is most resource-efficient within theframework of what is still possible.

In a preferred embodiment, prior to the selection of the controlquantity, the data sets taken into account in the selection of thecontrol quantity from the dependency table and/or the area of thesystematic dependence taken into account in the selection of the controlquantity are first limited to an area that an expected gain inavailability is not more than 20% above the availability with which acurrent itinerary of the motor vehicle can be carried out withoutunintentional impairment of sensor functionality and/or until athreshold of availability is reached, preferably not more than 10% andparticularly preferably not more than 5%,

-   -   in particular by applying a method for determining an expected        gain in availability, preferably according to the fourteenth        aspect of the invention, whereby the sum of the current        availability and the expected gain in availability is sufficient        to achieve a distance or an operating time to be covered by the        motor vehicle in such a way that a threshold of availability is        not exceeded.

Motor vehicles, in addition to active motor vehicle operation, inparticular when the motor vehicle is used to cover a distance, alsocontaminate in passive motor vehicle operation when the motor vehicle isparked at a point, in particular when the motor vehicle is exposed tothe weather unprotected.

With regard to the use of resources for the cleaning of a motor vehicle,it could be resource inefficient if the motor vehicle or a part thereofis cleaned shortly before the end of the planned operation of the motorvehicle, in particular if it is likely before the next active operationthat the motor vehicle will be heavily polluted by the passive operationof the motor vehicle, so that at least one cleaning process must bestarted at the beginning of the next operation of the motor vehicle inorder to restore the availability of a driver assistance system.

In other words, possible over-cleaning could be prevented before the endof active vehicle operation in order to save both advantageous andholistic resources for cleaning. The procedure proposed here makes thispossible.

Alternatively, there is provision for a modification according to afurther optional embodiment to moisten the surface which is only in aneffective connection with an unnecessary sensor from time to time with aspray of a cleaning fluid.

In this way, it can be advantageously achieved that a surface that isnot in an active connection with one of the necessary sensors does notdry out, thus advantageously preventing the incrustation of thecontamination present on this surface. In this way it can beadvantageously achieved that another cleaning process aimed at thedirect cleaning of the surface can get by with less cleaning resources,since it does not have to remove an encrusted layer of dirt in a shorttime, but rather an already soaked or pre-soaked dirt.

In other words, no cleaning process is proposed here in particular,which is aimed at the immediate cleaning of the surface, but a cleaningprocess, which makes it easier for a later cleaning process aimed at theimmediate cleaning of the surface to achieve a better cleaning result,in particular a higher gain of availability, with less resourceexpenditure.

In combination, a more efficient cleaning process can thus be madepossible.

To this end, the empirical values from the dependency table or the areaof the system behaviour mapped by the systematic dependence that can beselected by the procedure are limited to an area, so that an expectedgain in availability is not more than 20% above the availability withwhich a current itinerary of the motor vehicle can be carried outwithout unintentional impairment of sensor functionality and/or until athreshold of availability is reached, preferably not more than 10% andparticularly preferably not more than 5%.

Preferably, the expected gain in availability for each evaluatedcleaning process can be determined by applying the method according tothe fourteenth aspect of the invention.

Thus, it can be advantageously achieved that the cleaning processselected by the method does not lead to a significant over-cleaning ofthe surface in an active connection with the sensor on the one hand, andthat on the other hand, with a certain degree of safety before reachingthe target, no post-cleaning is necessary to maintain the driverassistance systems.

In this way, resources can be saved for the cleaning of surfaces thatare effectively connected to a sensor.

It should be pointed out that the above values for the considered areaof the expected gain in availability of the sensor due to the cleaningprocess should not be understood as sharp limits, but rather should beable to be exceeded or fallen below on an engineering scale withoutleaving the described aspect of the invention. In simple terms, thevalues are intended to provide an indication of the size of theconsidered expected gain in availability of the sensor due to thecleaning process proposed here.

Method for optimizing a resource requirement for a cleaning process of asurface of a motor vehicle according to one of the claims 1 to 6,characterized in that prior to the selection of the control quantity,the data sets taken into account in the selection of the controlquantity from the dependency table and/or the area of the systematicdependence taken into account in the selection of the control quantityare first limited to an area that an expected gain in availability issufficient to bridge a distance or an operating time to the nextcleaning process without falling below a threshold of availability andnot more than 20% above the gain in availability necessary to bridge thedistance or the operating time to the next cleaning process withoutfalling below a threshold of availability, preferably not more than 10%and particularly preferably not more than 5%,

-   -   in particular by applying a method for determining an expected        distance or an expected operating time of the motor vehicle yet        to be covered when reaching a threshold of availability,        preferably by applying a method according to the eleventh aspect        of the invention,    -   in particular by applying a method for determining an expected        gain in availability, preferably by applying a method according        to the fourteenth aspect of the invention,    -   whereby the sum of the current availability and the expected        gain in availability is sufficient to achieve a distance or an        operating time to be covered by the motor vehicle in such a way        that a threshold of availability is not exceeded.

In some situations of motor vehicle operation it is advantageous,especially if the cleaning resources currently still available areparticularly scarce, if only minimally invasive cleaning processes arecarried out, so that there is a good chance that the next intermediategoal and/or the next opportunity for replenishing cleaning resources canstill be achieved with the existing cleaning resources.

In particular, it is conceivable that an autonomous motor vehicleoperation can be maintained until the next filling station with theminimal use of cleaning means that is just necessary. Even if theminimally invasive cleaning processes proposed here are not optimallyresource-efficient in the sense of the highest possible increase inavailability with minimum use of cleaning agents, the availableresources are nevertheless optimally efficiently used in the sense ofachieving the goal of the vehicle operator, who in particular stillwants to reach the next intermediate destination of his journey by meansof autonomous driving.

This can be achieved by prior to the selection of the control quantity,the data sets taken into account in the selection of the controlquantity from the dependency table and/or the area of the systematicdependence taken into account in the selection of the control quantityare first limited to an area that an expected gain in availability issufficient to bridge a distance or an operating time to the nextcleaning process without falling below a threshold of availability andnot more than 20% above the gain in availability to bridge the distanceor the operating time to the next cleaning process without falling belowa threshold of availability, preferably not more than 10% andparticularly preferably not more than 5%.

In other words, here the solution space is limited by two sides.

It should be specifically remembered that before selecting the controlquantity setpoint, an expected distance or an expected operating time ofthe motor vehicle yet to be covered when reaching a threshold ofavailability is preferably determined by means of a procedure accordingto the eleventh aspect of the invention.

Furthermore, it should be specifically considered that before thecontrol quantity setpoint is selected, an expected gain in availabilityis also determined during the execution of a cleaning process by meansof a procedure according to the fourteenth aspect of the invention.

The advantage of this is that the selection of a cleaning process can bemade in such a way that the motor vehicle can optimally achieve theminimum goal defined by the driver with the available resources.

It should be pointed out that the above values for the considered areaof the expected gain in availability of the sensor due to the cleaningprocess should not be understood as sharp limits, but rather should beable to be exceeded or fallen below on an engineering scale withoutleaving the described aspect of the invention. In simple terms, thevalues are intended to provide an indication of the size of theconsidered expected gain in availability of the sensor due to thecleaning process proposed here.

In a preferred embodiment, a first control quantity and a second controlquantity are selected, wherein a respective first control quantitysetpoint and a respective second control quantity setpoint define afirst and a second cleaning process for a sequence of cleaningprocesses, the second cleaning process being performed after completionof the first cleaning process.

Here it is concretely proposed to divide a cleaning process of a surfaceto be cleaned into two or more individual cleaning processes of atogether planned sequence.

A first cleaning process is defined by a first control quantity setpointand a second cleaning process by a second control quantity setpoint.

It should also be considered that both control quantity setpointscontain conditions which trigger the respective cleaning processeswithin the scope of the cleaning method, especially within the scope ofa cleaning method according to the first aspect of the invention. Inparticular, a temporal distance between the individual cleaningprocesses, a spatial distance or the achievement of a defined triggeringavailability is considered.

The advantage is that resources for cleaning can be saved if severalcleaning processes are more resource-efficient than a single cleaningprocess. It was surprisingly found out that this could appear in someconstellations of the respective input quantity or the respective inputquantities.

Optionally, the method being carried out in series or in parallel for aplurality of surfaces to be cleaned, in particular for two, three, four,five or more surfaces to be cleaned.

So far, the procedure has only been described to the extent that thecleaning process to be carried out is only optimised for one surface ata time.

Here it is specifically proposed that the procedure be applied to alarge number of surfaces to be cleaned, in particular sequentially or inparallel.

Expediently the control quantity is selected by means of amulti-criteria optimization procedure.

Here it is concretely suggested that the selection of an optimalcleaning process is carried out with the aid of a multi-criteriaoptimisation procedure.

Such a procedure is particularly suitable if different resources are tobe optimised simultaneously and independently of each other.

Preference should be given to the fact that a special washing lotion canalso be used in addition to a cleaning liquid.

By using a multi-criteria optimization method, it can be advantageouslyachieved that the different resources can be equally advantageouslyconsidered resource-efficient in the decision based on a developingParetofront.

According to the third aspect of the invention, it is preferablypossible to take other influencing variables into account for resourceoptimization, in particular a device type of the sensor, a temperatureof the cleaning fluid, the composition of the cleaning fluid, a speed ofmovement of a wiping element, a quantity of cleaning fluid, anorientation of the nozzle and the like.

With regard to the temperature of the cleaning fluid, the composition ofthe cleaning fluid, the speed of movement of the wiping element, theamount of cleaning fluid and/or the orientation of the nozzle, this canalso be a control quantity.

It goes without saying that the advantages of systematic dependence, inparticular systematic dependence according to the second aspect of theinvention, also apply to the use of systematic dependence, in particularthe use of systematic dependence proposed here according to the thirdaspect of the invention.

It should be noted that the subject-matter of the third aspect can beadvantageously combined with the subject-matter of the preceding aspectsof the invention, either individually or cumulatively in anycombination.

According to a fourth aspect of the invention, the task is solved by amethod for determining a cleaning strategy for cleaning a surface to becleaned of a motor vehicle, whereby the surface to be cleaned isselected in dependence of a cleaning mode, whereby a sensor isoperatively connected to the surface to be cleaned, whereby the sensorexhibits an actual availability, whereby the cleaning strategy exhibitsa control quantity setpoint defining a cleaning process for the surfaceto be cleaned, exhibiting the following steps:

-   -   Preferably check the actual cleaning mode;    -   Select the at least one sensor required for the currently        selected cleaning mode;    -   Check the actual availability of each selected sensor;    -   Determine the control quantity setpoint for resource efficient,        preferably resource-saving, cleaning of each surface to be        cleaned operatively connected to each selected sensor, in        particular by applying a method for optimizing a resource        requirement for a cleaning process of a surface of a motor        vehicle, preferably by applying a method according to the third        aspect of the invention; and    -   Preferably store the determined control quantity setpoint for        resource efficient, preferably resource-saving, cleaning of each        surface to be cleaned operatively connected to each selected        sensor, particularly preferably store the determined control        quantity setpoint in the cleaning strategy, preferably within a        database and/or an electronic evaluation and data processing        unit and/or an electronic control unit.

If the availability of a sensor falls below a threshold of availability,this may result in limited functionality of the sensor, which mayindirectly impair the functionality of at least one driver assistancesystem.

The third aspect of the invention describes a procedure for optimizing acleaning process with regard to the consumption of resources for asurface to be cleaned that is in operative connection with a sensor.

The third aspect of the invention is to provide one or moreresource-optimal cleaning processes for one or more surfaces to becleaned.

However, the procedure according to the third aspect of the inventiondoes not take into account whether a particular surface connected to asensor has to be cleaned at all or, in other words, whether the sensor'savailability should be increased by carrying out the cleaning process,preferably by carrying out the cleaning process after the first aspectof the invention, for the current or planned use of the vehicle.

The fourth aspect of the invention is based on the idea that not everysensor is needed at all times for current or planned vehicle operation.

If a surface with a sensor that is currently not required is to becleaned, cleaning resources are also required for this purpose.

The fourth aspect of the invention makes use of this context to savecleaning resources and makes it possible that only the surface of amotor vehicle is cleaned by a cleaning process, in particular by acleaning method according to the first aspect of the invention, which,according to a selected cleaning mode, also has an active connection toat least one sensor whose functionality is desired for the current orplanned vehicle operation.

This allows advantageously the saving of cleaning resources, especiallysince it is allowed that the availability of a sensor, whosefunctionality is currently not needed, may also fall below a thresholdof availability.

For this purpose, a cleaning strategy for cleaning a surface to becleaned of a motor vehicle is determined by means of the procedureproposed here, which determines for the entire motor vehicle, dependingon a cleaning mode, whether a surface is to be cleaned and, if a surfaceis to be cleaned, how, that is, with which cleaning process this surfaceis to be cleaned, is also determined, preferably by means of thedetermination of a corresponding control quantity, preferably using aprocedure according to the third aspect of the invention.

Depending on a cleaning mode, the surface which is in an activeconnection to a sensor required for the current use of the vehicle isselected for this purpose and is also reserved for cleaning. In thiscontext, a corresponding sensor can also be referred to as a “selectedsensor”.

Furthermore, a control quantity setpoint is determined for each selectedsensor, preferably control quantity setpoint for resource efficient,preferably resource-saving, cleaning, by applying a method foroptimizing a resource requirement for a cleaning process of a surface ofa motor vehicle, preferably by applying a method according to the thirdaspect of the invention.

Preferably, each control quantity setpoint thus determined for eachselected sensor is stored in a cleaning strategy.

It goes without saying that a cleaning strategy becomes invalid as soonas the cleaning mode changes. As soon as the cleaning mode is changed, adifferent cleaning strategy must be applied within the scope of acleaning method, preferably within the scope of a cleaning methodaccording to the first aspect of the invention, or a new cleaningstrategy must be determined according to the proposed procedure.

It is expressly pointed out that a cleaning mode may coincide with adriving mode, but this is not necessarily the case, which is why theseterms are used separately here.

Preferably, the assignment of the selected sensors can be taken from anassociated list, which can preferably be taken from the database and/orthe electronic evaluation and data processing unit and/or the electroniccontrol unit.

Preferably it is suggested that a cleaning strategy can overwrite acommand of the motor vehicle and/or the driver as a last minute remedyto clean a surface of a selected sensor whose availability has reachedand/or fallen below a threshold of availability.

Furthermore, it is preferred that a clean strategy can provide that italso decides on the cleaning of a sensor which is not a selected sensor,especially if one of the selected sensors has a malfunction.

Preferably, before the control quantity setpoint is determined, adistance and/or an operating time is first determined which the motorvehicle can still cover as a function of the actual availability of theselected sensor until an expected availability then reaches a thresholdof availability at which the surface which is operatively connected tothe associated sensor is to be cleaned, in particular by applying amethod to determine an expected distance or an expected operating timeof the motor vehicle yet to be covered when reaching a threshold ofavailability, preferably by applying a method according to the eleventhaspect of the invention.

To date, the range of a vehicle achievable with the available cleaningresources has not been taken into account when determining a cleaningstrategy.

This is precisely what is being proposed here.

When operating a motor vehicle, a distinction can be made betweenoperating modes of the motor vehicle, for example between an activemotor vehicle operation, which is characterised by the fact that themotor vehicle completes a driving distance, and a passive motor vehicleoperation, in which the vehicle parked waits for the next active motorvehicle operation.

The motor vehicle pollutes both in active and passive motor vehicleoperation. For reasons of resource-optimal cleaning of a surface of amotor vehicle, it is specifically proposed that a surface is notover-cleaned, which is characterised by the fact that the surface of amotor vehicle is thoroughly cleaned shortly before reaching theobjective of active motor vehicle use.

Instead, it is proposed here that a cleaning process could pursue thegoal of cleaning the surface only to such an extent that theavailability obtained by the cleaning process is sufficient to achievethe goal of active vehicle operation. For this purpose, an associatedcontrol quantity setpoint can be determined in particular by means of amethod according to the third aspect of the invention.

A further effect results from the fact that different cleaning modesrequire different amounts cleaning resources. In particular, a cleaningmode that is designed to maintain autonomous vehicle operation requiresmore cleaning resources than a cleaning mode that is designed tomaintain at least one driver assistance system, which is merely intendedto assist the driver in driving the vehicle but does not allowautonomous vehicle operation.

As a result of this, it is proposed here,

-   -   according to a step before determining the control quantity        setpoint, first determine the expected distance and/or the        expected operating time which the motor vehicle can still cover        as a function of the actual availability of the selected sensor        until an expected availability then reaches a respective        threshold of availability, preferably by applying a method        according to the eleventh aspect;    -   to check the amount of available cleaning resources according to        a further step before determining the control quantity setpoint,        in particular with corresponding sensors, particularly preferred        with level sensors or the like;    -   to determine the cleaning strategy with the corresponding        control quantity setpoints depending on the currently selected        cleaning mode and in connection with this also the resource        requirements for the cleaning;    -   to compare whether sufficient resources are available to meet        the resource requirements of this cleaning strategy for reaching        the destination; and    -   if this is not the case, preferably to offer the driver a        cleaning mode with which he can reach his destination with the        available resources and/or to request him to refill        corresponding resources, the cleaning strategy offered being        achieved by using the selectable cleaning modes in a descending        order according to the resource requirement to determine a        cleaning strategy until a cleaning strategy is found with which        the motor vehicle can still reach his destination without one of        the selected sensors reaching an availability which is below an        associated threshold of availability.

In this way it can be advantageously achieved that the driver of a motorvehicle in a situation in which the necessary resources according to theselected cleaning mode are not sufficient to reach the destination candecide whether he wants to carry out a service stop to refill therequired resources, with which the currently selected cleaning mode canbe maintained, or whether he wants to dispense with the availability ofdriver assistance systems and thus arrive at the destination possiblyfaster if necessary.

Optionally, the threshold of availability depends on the selectedcleaning mode.

Different cleaning modes may have different error tolerances for aselected sensor.

In particular, it could be specifically considered that the faulttolerance for a selected sensor in a cleaning mode which is set up forfully autonomous motor vehicle operation is lower than in a cleaningmode which is set up for motor vehicle operation which does not permitfully autonomous motor vehicle operation.

Here it is proposed that a threshold of availability of each sensor canhave different values for different cleaning modes.

In this way it can be advantageously achieved that resources forcleaning can be saved by different thresholds of availability fordifferent cleaning modes.

Expediently, the cleaning mode is read from an electronic control unit.

It is suggested here that a cleaning mode can be read from an electroniccontrol unit. This makes it advantageous that a cleaning mode can bedefined in an electronic control unit and used from there in the scopeof a cleaning method, especially a cleaning method according to thefirst aspect of the invention, as well as in the scope of a method fordetermining a cleaning strategy, especially a method according to thefourth aspect of the invention.

Furthermore, it can be advantageously achieved that a cleaning mode canbe defined in an electronic control unit, in particular by themanufacturer of a motor vehicle, so that the manufacturer of a motorvehicle can also influence the cleaning of sensor surfaces, inparticular since these are safety-relevant aspects which could alsoreach into the area of manufacturer liability in the event of amalfunction.

Optionally, the cleaning mode is acquired from a selection means.

The following terms are explained in more detail:

A “selection means” is to be understood as a device with which thecleaning mode can be selected. Preferably, a rotary switch or a selectorslide or an electronic input unit or the like could be considered here.

Here it is specifically proposed that the cleaning mode can be takenfrom a selection means, in particular a selection means, which lieswithin the direct sphere of influence of the driver of the vehicle, sothat the driver can influence the cleaning mode and thus indirectly thecleaning strategy according to his needs by adjusting the selectionmeans.

According to a preferred variant of the embodiment, the cleaning mode isset up to enable fully autonomous motor vehicle operation, wherein eachsurface which is operatively connected to the sensor relevant for fullyautonomous motor vehicle operation is to be cleaned.

It is proposed here that the cleaning mode is set up for a fullyautonomous motor vehicle operation.

If a motor vehicle is set up and registered for fully autonomous motorvehicle operation at all, this may preferably mean that all sensorsinstalled on a motor vehicle are selected and thus the availability ofall sensors must be guaranteed.

In other words, this can lead to a situation where such a motor vehiclehas to cease fully autonomous motor vehicle operation if it falls belowa threshold of availability, at least until the correspondingavailability is again above the threshold of availability.

For the cleaning system, this means that the availability of a sensormust be prevented from falling below an associated threshold ofavailability. The same applies as an objective for the cleaning method,in particular the cleaning method according to the first aspect of theinvention, and consequently also for the method proposed here fordetermining a cleaning strategy.

According to another preferred variant of the embodiment, the cleaningmode is set up to enable comfortable motor vehicle operation for adesignated driver of the motor vehicle, wherein each surface which isoperatively connected to the sensor relevant for comfortable motorvehicle operation is to be cleaned.

The cleaning mode proposed here concerns the comfortable operation ofthe motor vehicle.

Preferably, this means that the operation is comfortable for the driverof the motor vehicle. Comfortable here does not mean a fully autonomousmotor vehicle operation, but a motor vehicle operation characterised bythe fact that the driver of the motor vehicle predominantly controls themotor vehicle himself.

A comfortable vehicle operation, however, is understood to mean thefunctionality of several driver assistance systems that can make drivingmore comfortable for the driver, in particular a lane departure warningsystem or a distance warning system or the like.

In other words, it is proposed here that the cleaning system ensures theavailability of all selected sensors relevant for the cleaning mode setup to enable comfortable motor vehicle operation with the appropriatecleaning method, in particular with a cleaning method according to thefirst aspect of the invention.

According to another preferred variant of the embodiment, the cleaningmode is set up to enable motor vehicle operation which is as safe aspossible for a designated driver of the motor vehicle, wherein eachsurfaces which is operatively connected to the sensor relevant for motorvehicle operation which is as safe as possible is to be cleaned.

Here it is proposed that the availability of all sensors required forsafety-relevant driver assistance systems is monitored, whereby themethod proposed here is set up to ensure that the respectiveavailabilities do not fall below the associated values of the associatedthresholds of availability.

According to another preferred variant of the embodiment, the cleaningmode is set up to enable the motor vehicle to have the best possiblerange, wherein each surfaces which is operatively connected to thesensor relevant for motor vehicle operation with the best possible rangeis to be cleaned.

The cleaning mode proposed here enables the motor vehicle to achievemaximum range with its remaining cleaning resources.

This is preferably made possible by deactivating all driver assistancesystems for active vehicle operation that are not prescribed by law, sothat the associated sensors may also be available below any relevantthreshold of availability.

In an expedient embodiment, the method being carried out for a pluralityof surfaces to be cleaned, in particular for two, three, four, five ormore surfaces to be cleaned.

Here it is suggested that the method establishes a cleaning strategy fora plurality of surfaces to be cleaned. This can be done serially or inparallel.

This applies preferentially to all surfaces of a motor vehicle that arein an active connection with a (selected) sensor.

Optionally, the step of determining the control quantity setpoint takesa measured quantity into account, preferably a process quantity,particularly preferably a current humidity and/or a forecast humidityalong the planned itinerary and/or a current temperature in the vicinityof the motor vehicle and/or a forecast temperature along the planneditinerary and/or a current rainfall and/or a forecast rainfall along theplanned itinerary and/or a current snowfall quantity and/or a forecastsnowfall quantity along the planned itinerary.

Here it is provided that a measured quantity is taken into account whendetermining the cleaning strategy.

This enables a control quantity setpoint to be found, preferably basedon the current or expected weather conditions on the pre-planned route,which provides a better relationship between the increase inavailability for the individual selected sensor and the cleaningresources used than a control quantity setpoint which did not take ameasured quantity into account.

In detail, with the necessary adjustments, what has already been doneunder the third aspect of the invention applies here.

Preferably, the step of determining the control quantity setpoint takesa vehicle type into account.

In particular, the type of motor vehicle provides information about thebuilt-in cleaning system and the location and orientation of thesurfaces intended for cleaning in this context. In detail, this applieswith any necessary adjustments, which has already been carried out underthe second aspect of the invention.

It is understood that the determination of a control strategy can takeinto account any resources for the cleaning of one or more surfaces. Inparticular, it is important to consider that the cleaning system canalso cause a resource restriction, which could also be taken intoaccount when determining a cleaning strategy. Preferably, the flow rateof the fluid pump can be considered as a possible boundary condition,which may require that only a certain number of cleaning processes canbe carried out in parallel.

Preferably, it is suggested that a selected sensor is cleaned as a lastminute remedy by means of a predetermined reserve cleaning process ifthe respective availability falls below the corresponding threshold ofavailability.

It should be noted that the subject-matter of the fourth aspect can beadvantageously combined with the subject-matter of the preceding aspectsof the invention, either individually or cumulatively in anycombination.

According to a fifth aspect of the invention, the task is solved by amethod for indirectly deriving a systematic dependence for a systembehaviour of a system component of a cleaning system of a motor vehicle,wherein the cleaning system is adapted for cleaning of at least onesurface of the motor vehicle by means of a cleaning process, preferablyadapted for a resource efficient cleaning, particularly preferablyadapted for a resource-saving cleaning, whereby an output quantitydepends on an input quantity by means of the system behaviour of thesystem, exhibiting the following steps:

-   -   Determine the input quantity as a first parameter of the method        by means of at least one sensor;    -   Determine the output quantity as a second parameter of the        method, preferably determined by means of at least one sensor;    -   Digitalize where necessary and record the determined first and        second parameters by a data processing system, whereby the data        processing system exhibits an electronic data processing and        evaluation system and a database;    -   Store the determined first and second parameters in an ordered        manner with reference to one another in the database as a data        set of a dependency table;    -   Derive the systematic dependence between the first and second        parameters by means of the electronic data processing and        evaluation system from at least two data sets of the dependency        table stored in the database, preferably from at least 50 data        sets of the dependency table, particularly preferably from at        least 200 data sets of the dependency table, whereby the        electronic data processing and evaluation unit accesses the data        sets of the dependency table and determines the systematic        dependence from the data sets of the dependency table by means        of an algorithm; and    -   Preferably store the derived systematic dependence in the        database and/or the electronic data processing and evaluation        unit and/or an electronic control unit.

Motor vehicles are increasingly equipped with an increasing number ofsensors, also due to the increasing importance of driver assistancesystems, which depend on the information provided by the sensors.

The majority of these sensors rely on the functionality of a surfacethat is in an active connection with the individual sensor to avoidexcessive contamination.

In addition to the number of sensors, the number of installationlocations for sensors on the vehicle is also growing, as is the numberof surfaces to be cleaned by a cleaning system that are operativelyconnected to at least one of these sensors.

Consequently, the complexity of the cleaning system for a motor vehicleis constantly increasing. In particular, the number of nozzles and fluidconnections is increasing. This has been accompanied by a steadyincrease in the number and complexity of valve devices, cleaning fluidpumps and cleaning fluid reservoirs.

In the same measure with the increasing automation of the entire vehicleby sensors, the degree of automation of cleaning systems for motorvehicles has also risen, since the increasing automation of the motorvehicle also requires the increasing automation of individual cleaningprocesses. After all, a driver of a partially autonomous or autonomouslyoperated motor vehicle cannot be expected to keep an eye on the soilingcondition of the relevant surfaces, which are in an interrelationshipwith the sensors for monitoring and/or regulating driving operation.Therefore, automation through driver assistance systems also requiresautomation of a cleaning system for a motor vehicle.

In addition to these complexity drivers described above, the networkingof the systems with each other plays an increasingly important role.

Overall, both the number of sensors and systems involved and theircomplexity and degree of networking have risen steadily.

As a result, the susceptibility to errors and the associated maintenancerequirements of the system components involved in a cleaning system haveincreased. The increasing complexity of individual system components aswell as the increasing complexity of the entire cleaning system make itdifficult to identify possible errors, so that maintenance work on acleaning system has become more and more time-consuming over time.

Since different system components for a defined cleaning system of adefined motor vehicle can also come from different suppliers, the searchfor a possible error is made even more difficult.

Even though there are increasing expected values for the maintenance ofsuch cleaning systems, it has recently been shown that these cannotwithstand the constantly increasing system complexity and the constantlyaccelerating need for systematic changes in the area of a cleaningsystem for a motor vehicle.

Here a method to derive a systematic dependence for the description ofthe system behaviour for a system component of a cleaning system of amotor vehicle is proposed.

The system behaviour of a system component is a reaction of the systemcomponent to a specification for the system component, where thespecification for the system component can be described by the inputquantity and the reaction of the system component by the outputquantity.

In other words, the output quantity of the system component depends onthe input quantity by means of the system behaviour.

It is pointed out that a system component of a cleaning system can beunderstood as a single part of a cleaning system, as well as a singleassembly and the whole cleaning system. Especially since each of theabove mentioned variants has an individual system behaviour, which canbe analysed and the knowledge about the system behaviour can be usedadvantageously later.

Among other things, it is conceivable that a known system behaviour of asystem component, especially a known system behaviour in the form of asystematic dependence derived here, can be used for comparison with anobserved system behaviour of this system component. If there is adeviation between the known and thus initially expected system behaviourand the observed system behaviour, this could be an indication that thesystem component and/or the cleaning system has a conspicuous featureand/or a malfunction and/or a defect.

In this way, the systematic dependence proposed here, which is derivedon the basis of empirical values, offers in an advantageous way thepossibility to compare an observed behaviour of a system component withan expected value for the system behaviour of the system componentdescribed by the systematic dependence and thus to verify whether thesystem component and/or the cleaning system behaves in accordance withexpectations.

Preferably each system component exhibits an individual systematicdependence.

For each system component that is to be diagnosed on the basis of theempirical values translated into a systematic dependence, an individualsystematic dependence can preferably be derived according to this aspectof the invention.

The method proposed here can be used to derive systematic dependenciesfor different system components serially and/or in parallel.

The method proposed here for deriving a systematic dependence fromempirical values can be divided into two sections. In the first section,empirical values on the system behaviour of the system component arecollected and stored in a dependency table. The input quantity, whichleads to an activity of a system component, and the output quantity,which describes the reaction of the system component to the activitycaused by the associated input quantity, are stored in an orderly mannerwithin the dependency table.

In the second section of the method, the empirical values collected inthe dependency table are further processed into a systematic dependenceby means of an algorithm.

It should be expressly pointed out that empirical values can becollected within the framework of this procedure in regular operation ofthe system component during operation of the motor vehicle in which thesystem component is installed. Furthermore, it is also conceivable thatcorresponding empirical values can be collected during operation of thesystem component in the laboratory or with a numerical simulation usinga suitable numerical model and stored in a dependency table.

It goes without saying that the systematic dependence proposed here canonly take into account those quantities of an input quantity and thosequantities of an output quantity which can be recorded and thusevaluated. In particular, the acquisition of a quantity by means of asensor based on a physical and/or chemical principle of action should beconsidered. Furthermore, a determination of a quantity by means of anumerical sensor is also considered, which can record the values in anumerical model or, on the basis of measured quantities, can provide afurther quantity that is not measured but can be determined numericallydepending on at least one measured quantity.

While the empirical values are discrete experiences for a single inputquantity, the advantage of a systematic dependence is that a systematicdependence can reproduce the system behaviour of the system component ina range of the input quantity, in particular can reproduce itcontinuously and discretizably.

The systematic dependence proposed here is generated on the basis of thesampling points of the collected discrete empirical values by means ofan algorithm, whereby it is possible that the systematic dependence atthe sampling points defined by the corresponding input quantities mayhave different output quantities compared to the documented experiences.This can preferably be caused by an averaging of the experiences.

Preferably, an input quantity is understood to be a quantity that is atleast indirectly suitable for influencing the system component. It isnot necessary that an input quantity can be adjusted directly. An inputquantity can also result from the environmental conditions. It isespecially conceivable that a low temperature leads to ice formation inthe cleaning system, which can also change the system behaviour of asystem component.

It should be expressly pointed out that neither the input quantity northe output quantity according to the aspect proposed here arenecessarily limited to quantities that directly affect the systemcomponent under consideration or can be determined directly at thesystem component under consideration. Rather it should be consideredthat every input quantity and every output quantity can be consideredwithin this aspect, which could have an indirect influence on the systembehaviour of the considered system component or which could beinfluenced indirectly by the system component.

The first section of the procedure proposed here shows the followingsteps:

-   -   Determine the input quantity as a first parameter of the method        by means of at least one sensor, wherein in each case an input        quantity, which may have a plurality of dimensions and which is        indicative of a behaviour of at least one system component, can        be advantageously provided for further processing by means of a        sensor;    -   Determine the output quantity as a second parameter of the        method, preferably determined by means of at least one sensor,        wherein in each case an output quantity, which may have a        plurality of dimensions and which describes the system behaviour        of a system component as a function of that input quantity which        is determined by means of the process step described above, can        be provided advantageously by means of a sensor for further        processing;    -   Digitalize where necessary and record the determined first and        second parameters by a data processing system, whereby the data        processing system exhibits an electronic data processing and        evaluation system and a database, wherein the input quantity and        the output quantity are advantageously prepared and stored for        digital processing; and    -   Store the determined first and second parameters in an ordered        manner with reference to one another in the database as a data        set of a dependency table, wherein the previously determined        quantities of the method can be stored in an advantageously        ordered manner relative to one another in such a way in the        dependency table that the output quantity is assigned to the        input quantity whose system behaviour of the system component        caused by it describes it.

Altogether, the first section of the procedure enables advantageouslythe generation of a dependency table consisting of empirical values forthe system behaviour of the considered system component.

The second section of the procedure proposed here shows the followingstep:

-   -   Derive the systematic dependence between the first and second        parameters by means of the electronic data processing and        evaluation system from at least two data sets of the dependency        table stored in the database, preferably from at least 50 data        sets of the dependency table, particularly preferably from at        least 200 data sets of the dependency table, whereby the        electronic data processing and evaluation unit accesses the data        sets of the dependency table and determines the systematic        dependence from the data sets of the dependency table by means        of an algorithm, whereby in this step the systematic dependence        is advantageously derived in a mathematical way by means of a        suitable algorithm.

The derived systematic dependence can then be advantageously stored sothat it can be recalled for further processing, in particular thesystematic dependence is stored in a non-volatile data memory.Preferably it is conceivable that the systematic dependence is stored ina database and/or in an electronic data processing and evaluation unitand/or in an electronic control unit.

Preferably the input quantity exhibits at least one measured quantity,preferably a process quantity and/or a control quantity.

Here it is suggested that the input quantity exhibits a measuredquantity, in particular a process quantity and/or a control quantity.

While a control quantity is directly suitable for influencing a cleaningsystem and thus at least indirectly a system component of the cleaningsystem, a process quantity is a quantity which at least indirectlydepends on a control quantity or which cannot be influenced by the usualmeans and only exhibits an effect on the system behaviour of a systemcomponent.

A process quantity is preferably a quantity which is present in acleaning system or around the cleaning system and which can beinfluenced at least indirectly by an input quantity.

It can be advantageously achieved that a dependency table and/or asystematic dependence can have a dependency to a directly measured inputquantity, especially to a process quantity and/or a control quantity,whereby important influence quantities for the system behaviour of asystem component can be taken into account.

In a preferred embodiment, the output quantity and/or the input quantityexhibits a resource requirement of the cleaning process of the surfaceof the motor vehicle, preferably a power consumption, preferably theresource requirement is determined depending on a control quantitysetpoint for the cleaning process of the surface.

The power consumption is a comparatively easy to determine quantity incombination with a system component of a cleaning system.

The power consumption of a system component can be used comparativelyquickly and easily to determine whether a change has occurred for anenergy-using system component, since the energy requirements of a systemcomponent fluctuate comparatively little under regular conditions.

Thus it can be advantageously achieved that the power consumption canalso be taken into account for the description of the system behaviourof the system component, whereby also in the context of a diagnosis ofthe system component, in particular a diagnosis according to the sixthaspect of the invention, the power consumption required by the systemcomponent can be used advantageously for the comparison between theexpected system behaviour and the actual system behaviour.

Optionally the output quantity and/or the input quantity exhibits aprocess quantity, preferably a flow pressure and/or an electric currentand/or a time of operation and/or a temperature and/or a fill levelsignal and/or a reaction time and/or a sensing time and/or a signal of aleaking through sensor and/or a signal of a flow gauge and/or a numberof actuations and/or a spray pattern and/or a heat monitoring signal,preferably a heat monitoring signal with reference to a reference area,and/or a signal of a debris sensor and/or a signal of a check valveand/or a signal of a drip sensor and/or a signal of a distance sensorand/or a signal of a force sensor.

In the context of an output quantity and/or an input quantity, a processquantity is also a valuable indicator for assessing the system behaviourof a system component of a cleaning system for a motor vehicle.

In particular, any process quantity should be considered in this contextwhich is preferably easy to determine or which is particularlymeaningful.

Specifically, the level signal of a cleaning fluid reservoir could beconsidered. If the cleaning system is not in active use at the moment,whereby in particular no cleaning fluid pump is actively in operation,and a decrease of the level signal for the cleaning fluid reservoir canbe observed nevertheless, this speaks comparatively simply for anundesired leak in the cleaning system, through which cleaning fluidescapes.

Alternatively, the signal of a flow velocity sensor in a flow channelfor cleaning fluid could also be considered, in particular bydetermining the static pressure on the wall of the flow channel forcleaning fluid. If, for example, a cleaning fluid pump is in activeoperation and all possible valves in the cleaning system are set so thata cleaning fluid should flow through the flow channel for cleaningfluid, and if the signal of the flow velocity sensor does not indicatethis, then there is a deviation between the expected and the actualsystem behaviour. This can have several causes, such as a leak in thecleaning fluid system or an empty cleaning fluid reservoir.

It should be explicitly mentioned that also with regard to the otherprocess quantities cause-effect correlations to the system behaviouroccur.

It can thus be advantageously achieved that a process quantity in theform of an output quantity can be included in a dependency table and/ora systematic dependence for the assessment of the system behaviour,whereby the diagnosis of the cleaning system can be improvedadvantageously in a downstream step.

In an optional embodiment the input quantity exhibits a humidity and/ora temperature in the vicinity of the motor vehicle and/or a rainfalland/or a snowfall quantity.

It has been shown that in particular environmental conditions such aspreferably humidity and/or temperature and/or rain and/or snow can havean influence on the system behaviour of a cleaning system, in particularenvironmental conditions in the direct vicinity of the motor vehicle.

In particular, a low temperature may lead to local freezing within thecleaning system, causing a local flow blockage.

In addition, further dependencies and influences of quantities on eachother can be taken into account.

By including the above quantities in the input quantity, the accuracy ofthe systematic dependence can be advantageously increased.

In an expedient embodiment the input quantity exhibits a vehicle type.

The type of motor vehicle determines the concrete design and arrangementof the individual system components of a cleaning system.

Thus in different constellations and/or arrangements of systemcomponents also a different influence of the system behaviour of a firstsystem component can be caused by the system behaviour of a secondsystem component. The vehicle type provides information about theconstellation and/or arrangement of the system components of a cleaningsystem and therefore represents a simple possibility to clearly recordcorresponding interactions.

In this respect, an interaction between a first system component and asecond system component is also determined by the vehicle type.

The inclusion of the vehicle type thus allows an advantageous increasein the mapping accuracy of the systematic dependences proposed here andthus also of the dependency table.

Preferably the input quantity exhibits an availability of the sensor.

If it is suggested here that the input quantity exhibits anavailability, this means preferably the availability before starting ofa cleaning process using the cleaning system.

The effectiveness of a cleaning process implemented by means of acleaning system depends not only on other influencing variables but alsoon the availability of a sensor whose surface is to be cleaned in anactive connection with it.

The availability of a sensor is a measure of the degree of soiling of asurface connected to a sensor.

It has been shown that a different availability of a sensor at thebeginning of a cleaning process exhibits an influence on the cleaningresult. In other words, a possible gain of availability can be differentfor a cleaning process that is carried out in the same way.

Among other things, it is suggested that the input quantity exhibits theparameters of a cleaning process and/or the output quantity exhibits thegain of availability.

This makes it possible that the system behaviour of the cleaning systemand/or a system component of the cleaning system can be evaluated on thebasis of the cleaning result, especially depending on the parameters ofthe cleaning process.

This allows advantageously that the system behaviour of a cleaningsystem can already be evaluated with the already installed sensors,especially with the sensors for the support of driver assistancesystems.

In this way it can be advantageously achieved that for the evaluation ofthe system behaviour of a system component of the cleaning system noextra sensors necessary only for the evaluation of the cleaning systemhave to be added.

It should be expressly pointed out that this aspect is particularlyrelated to the second, third, ninth and tenth aspects of the invention.It goes without saying that this aspect is also related to the otheraspects of the invention and that mutual relations exist.

Optionally the input quantity exhibits a current coordinate of the motorvehicle.

It has also been shown that the coordinate of a motor vehicle exhibitsan influence on the system behaviour of a system component of a cleaningsystem.

Preferably the weather conditions could be taken into account, whichdepend on the coordinate of a motor vehicle. In particular, it has beenshown that the system behaviour of a system component of a cleaningsystem depends on temperature and/or humidity and/or solar radiationand/or precipitation and/or snowfall.

According to a comparatively simple procedure, the weather conditions ata coordinate of the motor vehicle correlate with the current latitude onthe planet, which can be determined by the coordinate of the motorvehicle.

Thus, it can be advantageously achieved that on the basis of thecoordinate of a motor vehicle and on the basis of the correlation to theweather conditions, a related influencing variable on the systembehaviour of a system component of a cleaning system can be taken intoaccount, whereby the accuracy of the dependency table and/or thesystematic dependence can be improved advantageously for the systembehaviour.

According to a more precise approach, it is also suggested that themotor vehicle uses local information about the current and/or predictedweather at its coordinate. Thus, when determining the dependency tableand/or the systematic dependence, the influencing variables which are inan effective relationship to the system behaviour of a system componentof a cleaning system and which can be determined directly or indirectlyby the coordinate of the motor vehicle can be used to improve themapping accuracy for the predicted system behaviour.

It goes without saying that this aspect is related to the other aspectsof the invention and that mutual relations exist.

In a preferred embodiment the output quantity exhibits the availabilityof the sensor and/or a gain in availability due to the cleaning process.

Here it is suggested that the output quantity exhibits the availabilityof a sensor and/or the gain of availability due to the use of a cleaningsystem.

If it is suggested here that the output quantity exhibits anavailability, this means preferably the availability after completion ofa cleaning process using the cleaning system.

In this way, it can be advantageously determined how the systembehaviour of a system component of a cleaning system depends on thecleaning success of a cleaning process performed by a cleaning system.The gain of availability results from the difference between theavailability after the cleaning process and the availability before thecleaning process.

In an expedient embodiment the systematic dependence is determined bymeans of a regression analysis.

Here it is suggested to use a regression algorithm as algorithm for theindirect derivation of a systematic dependence.

An algorithm which has already been tested in a large number ofapplications and which can be optimally selected and/or adaptedaccording to the system behaviour considered here can thus beadvantageously applied so that a systematic dependence of high qualitycan be determined.

Preferably, the systematic dependence is determined in form of a curve,preferably a curve and a coefficient of determination of the curve.

The advantage of this is that the systematic dependence is indicated bya curve as a function of at least one input quantity for the systembehavior of a system component; in particular, this curve has no gaps,so that a clear assignment between an input quantity and an outputquantity can be achieved, in particular a continuous and differentiabledependency between an input quantity and an output quantity due to thesystem behavior of the system component, so that the systematicdependency is ideally adapted for any mathematical methods for the useof the same.

The evaluation of a coefficient of determination from the determineddata and the curve determined by means of a regression model provides anindication for the precision of the systematic dependence, assuming thata sufficient number of data sets is available. It can be advantageouslyevaluated how meaningful a correlation between an input quantity and anoutput quantity is and how well existing or recorded data can bereproduced. In addition, in the case of a large coefficient ofdetermination, the curve also allows statements to be made about themargins of existing data. It is conceivable, for example, that data canbe supplemented numerically and/or extrapolated at the margins ofexisting data.

Expediently the systematic dependence is determined by means of anoptimization process.

Here it is suggested that the parameters of a systematic dependence aredetermined by means of an optimization procedure, especially by means ofa minimization procedure, which minimizes the cumulated deviation of theempirical values considered by data sets from the systematic dependence.In this way, it is advantageously possible to determine a systematicdependence which can be derived in an optimal way, in particular with aminimum cumulated deviation from the initial experience values.

Preferably, the parameters of the systematic dependence are determinedby maximizing the resulting coefficient of determination.

Preferably, the systematic dependence is determined by means of aself-learning optimization method.

Among other things, it is proposed to use an algorithm that exhibits thecharacteristics of an algorithm from the class of machine learning.Thus, the algorithm is able to derive a systematic dependence betweenthe input quantity and a difference in availability due to soiling.

The advantage of this is that the complex task of indirectly deriving asystematic dependence by using self-learning optimization methods doesnot have to be laboriously adapted by humans to new conditions. Thus,time and money can be saved in the indirect derivation of systematicdependence.

The quality of the derived systematic dependence can be improved by theaspect proposed here, since an optimization procedure endeavors todetermine the optimal systematic dependence even in a multi-criteriaenvironment and under a variety of boundary conditions.

In this way, it is also conceivable that an optimization can be carriedout under a plurality of equal objectives and/or boundary conditions(multi criteria optimization). In particular, a class of algorithms isconsidered which can determine a Paretooptimum and/or a Paretofront. Inparticular, a class of algorithms in the area of simplex methods and/orevolutionary strategies and/or evolutionary optimization algorithmsand/or the like are suggested here for deriving the systematicdependence.

Optionally, the systematic dependence is derived using data sets of thedependency table from an already existing database, preferably data setsof an already existing database are accessed previously.

The advantage of this is that data from an existing database can also beused to derive the systematic dependence. Thus, it can be achieved thatempirical values do not have to be collected at a specific motor vehiclefirst and transferred into data of a database and later into asystematic dependence. In this way, existing data and empirical valuescan be used to derive a systematic dependence on the soiling processwithout first having to collect empirical values representing thesystematic dependence of the soiling process.

In an optional embodiment the already existing database is continuouslyexpanded.

Advantageously, it can be achieved that the number of derivablesystematic dependencies increases over time.

Furthermore, it can be advantageously achieved that the accuracy of asystematic dependence can increase due to the larger number of empiricalvalues known by means of data sets.

Expediently, a new data set replaces the data set in the dependencytable which deviates most from the derived systematic dependence.

In particular, the fact that the experience value is exchanged with thelargest Euclidean distance to systematic dependence should be taken intoaccount.

Advantageously, it can be achieved that the systematic dependencebecomes more and more precise over time, which can be expressed by anincrease in the coefficient of determination.

Furthermore, this can have the advantage that even weakly correlatingsystematic dependencies can be better identified over time.

It is also proposed that the output quantity and/or the input quantityexhibits the frequency and/or the speed of the cleaning fluid pump.

This can advantageously improve the dependency table and/or systematicdependence accuracy as it has been found that the frequency and/or thespeed of the cleaning fluid pump can influence the system behaviour of asystem component.

It is further suggested that the output quantity and/or the inputquantity exhibits the dimension of a nozzle and/or the wash fluid typeand/or the wash fluid quality.

This can advantageously improve the dependency table and/or systematicdependence accuracy since it has been found that the dimension of anozzle and/or wash fluid type and/or wash fluid quality can influencethe system behaviour of a system component.

It is suggested that the output quantity and/or the input quantityexhibits the pump diaphragm material and/or the hose material.

This can advantageously improve the dependency table and/or systematicdependence accuracy as it has been found that the pump diaphragmmaterial and/or the hose material can influence the system behaviour ofa system component.

It should be noted that the subject-matter of the fifth aspect can beadvantageously combined with the subject-matter of the preceding aspectsof the invention, either individually or cumulatively in anycombination.

According to a first alternative of a sixth aspect of the invention, thetask is solved by a method for diagnosing a system behaviour of a systemcomponent of a cleaning system of a motor vehicle,

-   -   wherein an output quantity depends on an input quantity by means        of the system behaviour of the system component of the cleaning        system,    -   wherein exceeding an upper threshold quantity by an actual        output quantity and/or falling below a lower threshold quantity        by the actual output quantity indicates that an actual system        behaviour deviates from an expected system behaviour,    -   exhibiting the following steps:        -   Preferably determine the input quantity;        -   Determine the actual output quantity;        -   Retrieve the upper threshold quantity and/or the lower            threshold quantity, preferably depending on the input            quantity;        -   Compare the actual output quantity with the upper threshold            quantity and/or the lower threshold quantity;        -   Preferably calculate a deviation between the actual output            quantity and the upper threshold quantity, if the actual            output quantity has exceeded the upper threshold quantity,            and/or calculate the deviation between the actual output            quantity and the lower threshold quantity, if the actual            output quantity has fallen below the lower threshold            quantity; and        -   Preferably store a diagnostic signal if the actual output            quantity exceeds the upper threshold quantity and/or if the            actual output quantity falls below the lower threshold            quantity.

Here a procedure for the monitoring and diagnosis of a system componentof a cleaning system of a motor vehicle is proposed.

The number of system components of a cleaning system and also the numberof functions of a cleaning system increase due to the increasing numberof driver assistance systems in a motor vehicle.

At the same time, the number of different combinations of differentsystem components on the market to form a cleaning system alsoincreases, with different system components usually being provided bydifferent suppliers.

As a consequence, the complexity of a cleaning system has alsoincreased, as has the need for maintenance to maintain fault-free systemoperation.

This has increased the need for systematic at least partially automatedor automatable approaches for the early detection of a possible error ina system component of a cleaning system.

It was unexpectedly discovered that electrical and mechanicalabnormalities in the system behaviour of a system component of acleaning system are often connected. This finding can be used toevaluate a system component on the basis of mechatronic concepts.

If an evaluation of a cleaning system currently depends predominantly onvisual observation, an evaluation of a system component on the basis ofmechatronic concepts can advantageously lead to the fact that alreadyexisting or with little effort additional electrical signals of a systemcomponent of a cleaning system can also be used for the evaluation ofpossible mechanical faults. Previously, this was only possible throughvisual inspection by trained personnel.

In particular, a mechanical abnormality in the system behaviour of asystem component can often be advantageously identified by at leastpartially automated observation of the electrical behaviour of a systemcomponent. Thus, a multitude of different possible problems inconnection with a cleaning system can be detected by monitoringelectrical quantities.

In particular, it was unexpectedly determined that the time course of aninrush current of a cleaning fluid pump in the presence of a mechanicalblocking of a flow channel for cleaning fluid can show characteristicdifferences to the time course of the inrush current in the presence ofan error-free regular switching on of the cleaning fluid pump,especially in the case of a mechanical blocking of the flow channeluntil the designated outlet of the cleaning fluid in a nozzle. It can beespecially advantageous possible to differentiate between a partialblocking and a full blocking of the flow channel for cleaning fluid.

While the temporal course of the inrush current when the cleaning fluidpump is switched on in the regular case only results in a shortovershooting step response, the step response in the presence of amechanical interlocking can in particular show a temporally morepronounced course in which the current reaches the expected value of acontinuous operation of the cleaning fluid pump only with a measurabledamping.

The procedure proposed here can preferably be carried out autonomouslyand can therefore preferably be carried out autonomously within theframework of a self-diagnosis of the cleaning system and report if anabnormal system behaviour of a system component of a cleaning system isdiagnosed.

In particular, it should also be considered that the diagnosticprocedure proposed here can preferably be activated without theintervention of the driver of the motor vehicle by means of theelectronic control unit of the motor vehicle and/or the cleaning system.Furthermore, it should also be considered that the diagnostic procedureproposed here can preferably be activated manually by the driver of themotor vehicle.

The diagnosis proposed here compares the expected behaviour of a systemcomponent of a cleaning system with a system behaviour determined duringthe monitoring of this system component by means of an actual outputquantity. This comparison is performed using at least one value of anoutput quantity.

The expected system behaviour is based in particular on empirical valuesfor the evaluated system component. These empirical values can be basedon observations in regular operation of the motor vehicle or in thelaboratory or be the result of a numerical model.

If the comparison leads to the result that the monitored systembehaviour of the system component corresponds to the expected systembehaviour, it is concluded that the system component has no defectand/or no fault and/or the system component is not impaired by externalinfluences acting on the system component.

The expected system behaviour is determined according to the methodproposed here on the basis of an upper threshold quantity and/or a lowerthreshold quantity. If the signal of the actual output quantity lies orruns within the range defined by the upper threshold quantity and thelower threshold quantity, then the system behaviour of the consideredsystem component is not unexpected, whereby this range can also beunilaterally open, provided that only an upper threshold quantity or alower threshold quantity is specified.

Thus, the method proposed here requires a list with at least one upperthreshold value or at least one lower threshold value for an outputquantity. Each threshold value is an individual value for each outputquantity and can also preferably depend on the input quantity and thesystem component under consideration.

Preferably the upper threshold quantity and/or the lower thresholdquantity depends on a process quantity.

If a monitored output quantity exceeds an individually associated upperthreshold value or if a monitored output quantity falls below anindividually associated lower threshold value, then there is a deviationthat can be characterized by another output quantity if necessary.

Furthermore, it is conceivable that a resolution strategy is known fromexperience with which the particular deviation can be corrected,especially after the seventh and/or eighth aspect of the invention.

If the deviation of the monitored output quantity from the expectedoutput quantity and/or the characterisation of the deviating systembehaviour results in a known pattern of behaviour, this can beassociated with a recommendation for action. Such a recommendation foraction is also based on empirical values, whereby these empirical valuescan also be largely systematized.

With regard to systematized empirical values, it should be specificallyconsidered that, depending on the type and severity of the deviation ofthe monitored output quantity from the expected output quantity, acertain error can be inferred. Preferably this conclusion is valid or atleast transferable for a plurality of different system components and aplurality of different cleaning systems.

For example, it should be considered here that an increased powerconsumption of a cleaning fluid pump and thus a deviation of the systembehaviour leads to the conclusion that there is an error in the cleaningsystem. It is especially conceivable here that the cleaning fluid pumpwill age, whereby it is particularly conceivable in concrete terms thata higher energy requirement will have to be used for a controlled pumppressure of the cleaning fluid pump.

Alternatively, it is conceivable in this case that there is a blockagein the flow channel downstream of the cleaning fluid pump which causesan increased back pressure which influences the system behaviour of thecleaning fluid pump. Depending on the situation, a differentiation tolocalize the cause of the diagnosed deviation can be made by comparing adifferent output quantity. For this, experience values are necessary,which can be available in a list in particular.

This also shows that a deviation between an expected output quantity andan actual output quantity of a system behaviour of a system componentdoes not have to be caused by the monitored system component itself.

In case of a blockage in front of the pump, a possible resolutionstrategy to correct the deviation with on-board means can be to increasethe pump pressure in a targeted way, whereby the blockage can bereleased and washed out of the cleaning system. In particular, aselection of a resolution strategy according to the seventh aspect ofthe invention could be considered.

When implementing a resolution strategy, particular consideration shouldbe given to implementing the resolution strategy according to the eighthaspect of the invention.

If a selected and implemented resolution strategy is successful, asystem behaviour of the system component will result which correspondsto the expected system behaviour.

It should be expressly pointed out that the diagnostic method describedhere can be applied to any system component. If a sufficient number ofsensors or measuring devices, a sufficient number of experience valuesregarding the expected system behaviour of one or more system componentsand a list of potentially successful resolution strategies areavailable, a large number of occurring deviations can be corrected withon-board devices. Deviations of the system behaviour which cannot berepaired with on-board resources can also be detected at an early stageand repaired within the scope of regular or early maintenance, whereby apossible extension of possible damage in the other case can be preventedadvantageously.

It goes without saying that the input quantity, the output quantity, thelower threshold quantity and/or the upper threshold quantity and/or thedeviation can be scalar or vector quantities.

Furthermore, it is optionally suggested that a diagnostic signal bestored or passed on to an electronic control unit of the motor vehicle.

Preferably it is proposed to calculate a deviation between the actualoutput quantity and the upper threshold quantity if the actual outputquantity exceeds the upper threshold quantity, and/or to calculate adeviation between the actual output quantity and the lower thresholdquantity if the actual output quantity falls below the lower thresholdquantity.

The above quantities are scalar if only a single parameter is to beevaluated without a temporal course of this parameter. In all othercases, in particular when considering several parameters of the cleaningsystem and/or when considering at least one temporal course of aparameter, the above quantities are to be understood as vectorquantities.

The preferably proposed calculation of the deviation between the actualoutput quantity and the upper threshold quantity and/or the lowerthreshold quantity therefore also depends on whether the outputquantities are scalar or vectorial. It is proposed that the upperthreshold quantity and/or the lower threshold quantity be adjusted tothe dimensional characteristic of the actual output quantity, unlessthis is already the case, whereby it must be ensured that the upperthreshold quantity and/or the lower threshold quantity and the actualoutput quantity each have corresponding values.

In the case of a vectorial actual output quantity, the calculation ofthe deviation takes place separately for each component, i.e. dimensionfor dimension.

A deviation can occur for some or all components of the actual outputquantity, whereby at the same time a deviation is conceivable for acomponent because the corresponding component of the lower thresholdquantity is undershot and a deviation for a component because thecorresponding component of the upper threshold quantity is overshot.

If a deviation is determined with regard to at least one componentbetween the upper threshold quantity and/or the lower threshold quantityand the actual output quantity, a further investigation of thisdeviation is proposed.

This diagnostic signal may include that no deviation of the actualsystem behaviour from the expected system behaviour has been detected.

Furthermore, the diagnostic signal may include that a deviation of theactual system behaviour from the expected system behaviour has beendetected, whereby the type and expression of the deviation may also bestored in the diagnostic signal.

Preferably it is suggested that the diagnostic signal exhibits adeviation.

Preferably the diagnostic signal exhibits an output quantity and/or acourse of an output quantity over time, wherein the course of the outputquantity over time exhibits at least two points in time, preferably atleast ten points in time and particularly preferably at least 20 pointsin time.

It should be pointed out that the above values for the amount of valuesover time should not be understood as sharp limits, but rather should beable to be exceeded or fallen below on an engineering scale withoutleaving the described aspect of the invention. In simple terms, thevalues are intended to provide an indication of the size of the amountof values over time range proposed here.

In particular, it should also be remembered that the diagnostic signalexhibits a plurality of temporal curves of the output quantity overtime, in particular together with the input quantity and/or the processquantity.

This makes it advantageously possible to observe and evaluate a changein the system behaviour of a system component, especially with regard topossible ageing effects and/or a remaining life expectancy of the systemcomponent, preferably depending on an input quantity and/or a processquantity.

Thus, an at least partially automated error detection regarding thesystem behaviour of a system component of a cleaning system for a motorvehicle can be made possible in an advantageous way, where possibleerrors can be detected autonomously at an early stage.

This also makes it possible to identify possible sources of follow-uperrors at an early stage, which can advantageously limit the spread ofan error.

In this way, the interval at which an optical inspection should becarried out by trained specialists can also be advantageously extended,thus reducing the overall maintenance costs for the cleaning system andthe expected availability of the cleaning system.

According to a second alternative of a sixth aspect of the invention,the task is solved by a method for diagnosing a deviation between anactual system behaviour and an expected system behaviour of a systemcomponent of a cleaning system of a motor vehicle,

-   -   wherein an output quantity depends on an input quantity by means        of a system behaviour of the system component of the cleaning        system,    -   wherein the actual system behaviour depending on the input        quantity is represented by an actual output quantity and the        expected system behaviour depending on the input quantity is        represented by an expected output quantity,    -   wherein the expected system behaviour is represented by at least        one data set of a dependency table or a systematic dependence,        preferably a systematic dependence derived by a method according        to the fifth aspect of the invention,    -   exhibiting the following steps:        -   Preferably determine the input quantity;        -   Determine the actual output quantity;        -   Determine the expected output quantity by:            -   Select the data set from the dependency table that best                matches the input quantity, read the output quantity                stored in the selected data set and take it as the                expected output quantity; or            -   Select the two data sets from the dependency table that                best matches the input quantity an determine the                expected output quantity using linear interpolation                based on the two selected data sets; or            -   Calculate the expected output quantity by inserting the                input quantity into the systematic dependence;        -   Calculate the deviation between the actual output quantity            and the expected output quantity; and        -   Preferably store a diagnostic signal if the deviation is            greater than 10% of the expected output quantity, preferably            5% greater than the expected output quantity, particularly            preferably 2% greater than the expected output quantity.

Parallel to the first alternative of the sixth aspect of the invention,this second alternative of the sixth aspect of the invention alsoproposes a procedure for the monitoring and diagnosis of a systemcomponent of a cleaning system of a motor vehicle.

It should be expressly pointed out that the unrestricted description ofthe first alternative of the sixth aspect of the invention describedabove is also valid for the second alternative of the sixth aspect andvice versa, whereby the actual output quantity is compared differentlynot with a lower threshold quantity and/or an upper threshold quantitybut with an expected output quantity.

In contrast to the first alternative, according to the secondalternative of the sixth aspect of the invention, it is proposed thatthe actual output quantity is compared with an expected output quantity,whereby a deviation between the actual output quantity and the expectedoutput quantity is determined.

The diagnosis proposed here compares the expected system behaviour of asystem component of a cleaning system with an expected system behaviour.This comparison is performed on the basis of at least one value of anactual output quantity in comparison to the corresponding value of theexpected output quantity.

The expected system behaviour is based in particular on empirical valuesfor the system component diagnosed with the proposed method. Theseempirical values can be based on observations in regular operation ofthe motor vehicle or in the laboratory or be the result of a numericalmodel suitable for mapping the regular system behaviour of the cleaningsystem.

Preferably the expected system behaviour and thus also the expectedoutput quantity depends on an input quantity by which the cleaningsystem is operated.

Preferably the expected system behaviour and thus the expected outputquantity depends on a process quantity.

According to this second alternative of the sixth aspect of theinvention further three in each case deviating variants are suggested,by means of which the expected output quantity can be determined on thebasis of empirical values.

According to a first and second variant it is conceivable that anexpected system behaviour of a system component is described by adependency table, especially a dependency table, which has been createdaccording to the first steps of the method according to the fifth aspectof the invention.

It should be explicitly mentioned that the dependency table may dependon the system component to be diagnosed, an input quantity and/or aprocess quantity.

Such a dependency table describes discrete empirical values for theexpected system behaviour of one system component at a time, so that anempirical value must first be selected from the dependency table beforecomparison with the actual output quantity.

With regard to the evaluation of the dependency table, the first andsecond variants for determining the expected output quantity differ fromeach other.

According to the first variant for the selection of an expected outputquantity, it is proposed to select from the dependency table theexperience value in the form of a data set which is best suited bycomparing the actual input quantity and/or the actual process quantitywith the input quantity and/or the process quantity of the respectivedata set, in particular best suited defined by the shortest Euclideandistance with regard to the input quantity and/or the process quantitybetween a data set stored in the dependency table and the actual inputquantity and/or the actual process quantity.

According to the second variant for the selection of an expected outputquantity, it is proposed to select the two best fitting and adjacentempirical values according to the description of the first variant inthe form of two data sets from the dependency table and to interpolatebetween these two empirical values according to the actual inputquantity and/or the actual process quantity.

According to a third variant for the selection of an expected outputquantity, it is proposed that an expected system behaviour of a systemcomponent is mapped by means of a systematic dependence, in particularby means of a systematic dependence derived according to the fifthaspect of the invention.

A systematic dependence can describe the expected system behaviourcontinuously as a function of the actual input quantity and/or theactual process quantity, so that a selection or interpolation betweenempirical values, as described above for the second variant, is nolonger necessary.

Just like the dependency table according to variants one and two, thesystematic dependence could be only valid for one system component, sothat for a consideration of a deviating system component a deviatingsystematic dependence or a deviating dependency table can or should beselected.

It is understood that the input quantity, the actual output quantity,the expected output quantity and/or the deviation can be scalar orvectorial quantities. The above quantities are scalar if only a singleparameter describing the system behavior of the system component is tobe evaluated without a temporal course of this parameter. In all othercases, in particular when considering several parameters of the cleaningsystem and/or when considering at least one temporal course of aparameter, the above variables are to be understood as vectorialquantities.

The calculation of the deviation between the actual output quantity andthe expected output quantity therefore also depends on whether theoutput quantities are scalar or vectorial. It is preferably suggestedthat the expected output quantity is adjusted to the dimensionalcharacteristic of the actual output quantity, if this is not already thecase, whereby in each case it must be ensured that the expected outputquantity and the actual output quantity each have quantitiescorresponding to each other.

In the case of a vectorial actual output quantity, the calculation ofthe deviation takes place separately for each component, i.e. dimensionfor dimension.

If a deviation is determined with regard to at least one componentbetween the expected output quantity and the actual output quantity, afurther investigation of this deviation is proposed.

According to the discussion already mentioned above, measurement errorsand expected fluctuations of a respective signal can also occur inregular operation when determining measured values.

Accordingly, not every nominal deviation between an expected outputquantity and an actual output quantity leads to a deviation of theactual system behaviour of a system component from its expected systembehaviour.

In order to quantify when it is a deviation of the actual systembehaviour of a system component from the expected system behaviour, itis suggested here to use a relative deviation between the actual outputquantity and the expected output quantity.

This relative comparison is also performed component by component. Itshould also be considered that a limit value above which a deviationbetween the actual system behaviour of the system component and theexpected system behaviour deviates could be specified for each componentin different sizes according to the available empirical values.

Among other things, a limit value of a deviation of 10%, preferably of5% and in particular of 2% is proposed.

It should be pointed out that the above values for the limit value of adeviation should not be understood as sharp limits, but rather should beable to be exceeded or fallen below on an engineering scale withoutleaving the described aspect of the invention. In simple terms, thevalues are intended to provide an indication of the size of the limitvalue of a deviation proposed here.

Preferably the limit value of a deviation is 15%. Furthermore preferablythe limit value of a deviation is 20%. Furthermore preferably the limitvalue of a deviation is 25%. Furthermore preferably the limit value of adeviation is 30%.

If the ratio between the actual output quantity and the expected outputquantity exceeds the limit value in at least one component, the actualsystem behaviour differs from the expected system behaviour of theconsidered system component.

Otherwise the actual system behaviour corresponds to the expected systembehaviour and it can be concluded that the considered system componentof the cleaning system has no defect and/or no malfunction and/or thesystem component is not impaired by external influences acting on thesystem component.

In particular, a deviation between an expected output quantity and anactual output quantity of a system behaviour of a system component neednot be caused by the monitored system component itself.

Rather it can be part of the further diagnosis which system component ofthe cleaning system shows or could show a possible error depending onthe deviation determined.

Please note that the diagnostic method described here can be used forany system component. If a sufficient number of sensors or measuringdevices, a sufficient number of experience values regarding the expectedsystem behaviour of one or more system components and a list ofpotentially successful resolution strategies are available, a largenumber of occurring deviations can be corrected with on-board devices.Deviations of the system behaviour which cannot be repaired withon-board resources can also be detected at an early stage and repairedwithin the scope of regular or early maintenance, whereby a possibleextension of possible damage in the other case can be preventedadvantageously.

Furthermore, it is optionally suggested that a diagnostic signal bestored or passed on to an electronic control unit of the motor vehicle.

This diagnostic signal may include that no deviation of the actualsystem behaviour from the expected system behaviour has been detected.

Furthermore, the diagnostic signal may include that a deviation of theactual system behaviour from the expected system behaviour has beendetected, whereby the type and expression of the deviation may also bestored in the diagnostic signal.

Preferably the diagnostic signal exhibits an output quantity and/or acourse of an output quantity over time, wherein the course of the outputquantity over time exhibits at least two points in time, preferably atleast ten points in time and particularly preferably at least 20 pointsin time.

It should be pointed out that the above values for the amount of valuesover time should not be understood as sharp limits, but rather should beable to be exceeded or fallen below on an engineering scale withoutleaving the described aspect of the invention. In simple terms, thevalues are intended to provide an indication of the size of the amountof values over time range proposed here.

In particular, it should also be remembered that the diagnostic signalexhibits a plurality of temporal curves of the output quantity overtime, in particular together with the input quantity and/or the processquantity.

This makes it advantageously possible to observe and evaluate a changein the system behaviour of a system component, especially with regard topossible ageing effects and/or a remaining life expectancy of the systemcomponent, preferably depending on an input quantity and/or a processquantity.

If the comparison between the actual output quantity and the expectedoutput quantity is completed, the diagnostic method can be stopped oralternatively continued with the same system component again or with adifferent system component.

Thus, an at least partially automated error detection regarding thesystem behaviour of a system component of a cleaning system for a motorvehicle can be made possible in an advantageous way, where possibleerrors can be detected autonomously at an early stage.

This also makes it possible to detect possible sources of follow-uperrors at an early stage, which can advantageously limit the propagationof an error.

In this way, the interval at which an optical inspection should becarried out by trained specialists can also be advantageously extended,thus reducing the overall maintenance costs for the cleaning system.

In a preferred embodiment, the deviation exhibits a temporal course,preferably the temporal course exhibits at least two points in time inthe process, preferably at least 10 points in time, particularlypreferably at least 20 points in time.

Here it is concretely proposed to consider the previously discusseddeviation now also as course of the deviation over time.

Preferably, the course of deviation over time can also be stored,preferably in a database.

Preferably, the temporal course is stored with the diagnostic signal.

In particular, it is suggested that the time course of the deviationbegins shortly before a planned change of an input quantity. Preferably,the time course of the deviation ends after the next planned change oftime.

In particular, it should be remembered that the output quantity isdiagnosed over a period of time which at least slightly exceeds twoplanned changes of an input quantity on both sides. In particular, thediagnosis of a time course of an output quantity starts before theswitching on of a cleaning fluid pump and ends after the switching offof the cleaning fluid pump.

Based on the time course of an output quantity, a systematic error of asystem component can be evaluated, in particular a systematic error thatexhibits a dependency on the damping of the system behaviour of thesystem component.

Furthermore, it is advantageous to consider that a temporal course doesnot run continuously, but rather records a certain output quantity aftereach activation of a system component.

In particular, it should be remembered that a fluid pressure downstreamof the cleaning fluid pump and/or a current and/or a fluid velocitydownstream of the cleaning fluid pump are recorded after each switch-onprocess in a defined time unit after the switch-on process and theindividual values recorded in each case are recorded and diagnosed as atime series.

In this way, a performance degrading of the cleaning fluid pump overlifetime can be advantageously evaluated so that a warning can beprovided if the cleaning fluid pump is expected to be replaced.

It should be pointed out that the above values for the amount of datapoints in time should not be understood as sharp limits, but rathershould be able to be exceeded or fallen below on an engineering scalewithout leaving the described aspect of the invention. In simple terms,the values are intended to provide an indication of the size of theamount of data points in time range proposed here.

The system behaviour of a system component can be evaluatedadvantageously on the basis of a temporal course of the output quantity,whereby a multiplicity of further analysis possibilities is offered, inparticular such analysis possibilities, which stand with thetransmission behaviour of the system component in relation.

In particular, the temporal course of the deviation could be evaluatedas a function of the input quantity and/or the output quantity, wherebydata which have the same or a very similar input quantity and/or processquantity is compared with one another.

Preferably, the temporal course exhibits at least 30 points in time.Preferably, the temporal course exhibits at least 40 points in time.Preferably, the temporal course exhibits at least 50 points in time.

Preferably, the findings of the analysis of the temporal course of thedeviation are stored together with the diagnostic signal and/or in thediagnostic signal.

Preferably, the temporal course of the deviation is examined for a stepresponse.

Here it is proposed to evaluate the temporal course of the outputquantity with regard to a step response, in particular with regard to astep response as a reaction to a change in an input quantity.

In particular, the value of the output quantity or the changed change ofthe output quantity could be examined for the change of the inputquantity.

Furthermore, it is proposed that the temporal course of the outputquantity be examined preferably with regard to the transmission behavioras part of the system behavior of the system component, whereby thedamping that affects the output quantity can be determined.

Preferably it can be diagnosed whether a nozzle is ‘partially orcompletely clogged for the cleaning fluid’. For example, a spike in thepressure behind the cleaning fluid pump indicates that a nozzle isblocked. The shape of the spike can provide an advantageous indicationof whether the flow channel behind the pump is completely or partiallyblocked.

The comparison of the characteristic characteristics may require acomparison of the course of the spike with one or more benchmark coursesof the pressure.

If a blockage of the nozzle is detected, a resolution strategy can beused according to the seventh and/or eighth aspect of the invention.

Alternatively, a warning can be generated requesting manual cleaning ofthe nozzle.

By monitoring the inrush current of a cleaning fluid pump over time, itis also possible to diagnose whether it is blocked, especially in frozenconditions.

In particular, a blocked cleaning fluid pump has a higher damping withregard to the inrush current.

If a blocked cleaning fluid pump is detected, it can in particular beswitched off, which has the advantage of preventing the cleaning fluidpump from burning out.

The system behaviour of a system component can be evaluatedadvantageously on the basis of a temporal course of the output quantity,whereby a multiplicity of further analysis possibilities is offered, inparticular such analysis possibilities, which stand with thetransmission behaviour of the system component in relation.

In particular, the step response could be evaluated as a function of theinput quantity and/or the output quantity, whereby data which have thesame or a very similar input quantity and/or process quantity iscompared with each other.

Preferably, the findings of the analysis of the temporal course of thedeviation are stored together with the diagnostic signal and/or in thediagnostic signal.

Expediently, at least two temporal courses of the deviation are examinedfor the presence of a drift of the deviation over time, preferably atleast five courses of the deviation, preferably at least 10 courses ofthe deviation.

Here it is suggested to evaluate the temporal course of the outputquantity with regard to a drift of the output quantity over time.

A drift is a systematic change of the output quantity as a reaction toan input quantity over the lifetime of the system component.

The temporal course of the output quantity can be compared withpreviously observed temporal courses of the output quantity over time,especially with a plurality of temporal courses of the output quantityover time.

If the deviation with time is continuously moving in one directionstarting from the expected system behaviour of the system component, adrift is present. According to the characteristic, it can beadvantageously determined how in particular an age-related change of thesystem behaviour of the system component develops.

Furthermore, it is advantageous to consider that a temporal course doesnot run continuously, but rather records a certain output quantity aftereach activation of a system component.

In particular, it should be remembered that a fluid pressure downstreamof the cleaning fluid pump and/or a current and/or a fluid velocitydownstream of the cleaning fluid pump are recorded after each switch-onprocess in a defined time unit after the switch-on process and theindividual values recorded in each case are recorded and diagnosed as atime series.

In this way, a performance degrading of the cleaning fluid pump overlifetime can be advantageously evaluated so that a warning can beprovided if the cleaning fluid pump is expected to be replaced.

In particular, the temporal course of the deviation could be evaluatedfor the presence of a drift as a function of the input quantity and/orthe output quantity, whereby data which have the same or a very similarinput quantity and/or process quantity is compared with one another.

Preferably, at least 20 temporal courses of the deviation are examinedfor the presence of a drift of the deviation over time. Preferably, atleast 30 temporal courses of the deviation are examined for the presenceof a drift of the deviation over time. Preferably, at least 40 temporalcourses of the deviation are examined for the presence of a drift of thedeviation over time.

It should be pointed out that the above values for the amount oftemporal courses of the deviation should not be understood as sharplimits, but rather should be able to be exceeded or fallen below on anengineering scale without leaving the described aspect of the invention.In simple terms, the values are intended to provide an indication of thesize of the amount of temporal courses of the deviation range proposedhere.

Preferably, the findings of the analysis of the temporal course of thedeviation are stored together with the diagnostic signal and/or in thediagnostic signal.

The cause for an actual system behaviour deviating from the expectedsystem behaviour may be based on the currently diagnosed systemcomponent or may have a cause which is based on a deviating systemcomponent, but which is transferred to the actually diagnosed systemcomponent according to a system-dependent transfer function between thecomponents.

If a corresponding transfer function is not known, it is suggested todiagnose further system components to limit the cause.

The diagnostic signal preferentially exhibits information about theinput quantity, which has an effect on the cleaning system and/or thesystem component during the diagnosis of the system component.

The diagnostic signal preferentially exhibits information about theprocess quantity, which has affected the cleaning system and/or thesystem component during the diagnosis of the system component.

It goes without saying that the advantages of systematic dependence, inparticular systematic dependence according to the fifth aspect of theinvention, also apply to the use of systematic dependence, in particularthe use of systematic dependence proposed here according to the sixthaspect of the invention.

It should be noted that the subject-matter of the sixth aspect can beadvantageously combined with the subject-matter of the preceding aspectsof the invention, either individually or cumulatively in anycombination.

According to a seventh aspect of the invention, the task is solved by amethod for selecting a resolution strategy from a list of resolutionstrategies contained in a database depending on a present diagnosticsignal, preferably depending on a present diagnostic signal receivedaccording to the sixth aspect of the invention, whereby the list ofresolution strategies contains at least one resolution strategyassociated with a diagnostic signal, whereby the resolution strategy isselected from the list of resolution strategies whose associateddiagnostic signal best matches the present diagnostic signal.

If the actual system behaviour of a system component of a cleaningsystem for a motor vehicle does not correspond to the expected systembehaviour, the deviation between the actual system behaviour and theexpected system behaviour can have several causes.

In particular, the cause for an actual system behaviour deviating fromthe expected system behaviour may be due to the currently diagnosedsystem component or may have a cause which is due to a deviating systemcomponent but which is transferred to the actually diagnosed systemcomponent according to a system-dependent transfer function between thesystem components.

Preferably the category of a cause for a deviation between the actualsystem behaviour and the expected system behaviour can be determined bya diagnostic signal, especially by a present diagnostic signal accordingto the sixth aspect of the invention.

A present diagnostic signal means the diagnostic signal which is subjectto a resolution strategy within the scope of this method. In particular,a present diagnostic signal may have been created using a methodaccording to the sixth aspect of the invention. In particular, a presentdiagnostic signal indicates that there is a deviation between the actualsystem behaviour and the expected system behaviour.

When determining the cause of a deviation between the actual systembehaviour and the expected system behaviour by means of the diagnosticsignal, the input quantity and/or the process quantity which has aneffect on the system component and/or the cleaning system whendetermining the diagnostic signal is particularly preferred.

It should be specifically considered that a present diagnostic signalcan be associated with causes for a deviation for the system behaviourof a system component on the basis of existing empirical values, andpreferably can be unambiguously associated.

Furthermore, it could be specifically considered that these empiricalvalues are systematised to such an extent that they are valid for aplurality of different system components and/or a plurality of differentcleaning systems or at least transferable.

In this way, it can be advantageously achieved that on the basis ofexisting experience with different system components of differentcleaning systems, in particular different cleaning systems of differentmanufacturers or suppliers, an unambiguous assignment can be madebetween a present diagnostic signal and a cause for the deviation of thesystem behaviour, in particular an unambiguous manufacturer-independentand type-independent assignment for the cleaning system and/or thespecific system component.

In particular, four different categories of causes of a deviationbetween the actual system behaviour and the expected system behaviourare proposed, which preferably can be distinguished by means of adiagnostic signal, especially preferred by means of a present diagnosticsignal according to the sixth aspect of the invention.

Specifically, it is proposed here to determine a category of a cause inthe presence of a present diagnostic signal.

According to a first category for a cause of a deviation between theactual system behaviour and the expected system behaviour there is adefect of a system component. In this respect, a multitude of differentdefects is conceivable.

In particular, it is conceivable that a cleaning fluid line has detacheditself from a system component of the cleaning system if a defect ispresent. Such a defect could also be repaired by an untrained person.

Furthermore it is conceivable that a leakage in a cleaning fluid line ispresent. In this case, a spare part is needed at least in the mediumterm and the defect cannot be repaired by an untrained person alone atleast in the medium term.

According to a second category for a cause of a deviation between theactual system behaviour and the expected system behaviour, there is anageing phenomenon of a system component.

Even if the majority of the system components of a cleaning system of amotor vehicle are designed in such a way that they survive the expectedlifetime of a motor vehicle, a system component still ages. In concreteterms, it is also conceivable that a system component ages faster thanintended, so that the expected lifetime of this system component isshorter than the planned lifetime of the motor vehicle. In this case,the replacement of such a component is unavoidable for the furtherregular operation of the cleaning system.

Preferably, an ageing phenomenon can be detected and/or evaluated on thebasis of a drift of the deviation over time, in particular on the basisof a drift of the deviation according to the sixth aspect of theinvention.

The course of the drift of the deviation over time is a particularlypreferred way of determining how big the remaining expectation is forthe usability of the system component.

According to a third category for a cause of a deviation between theactual system behaviour and the expected system behaviour there is adisturbance of a system component.

It should be expressly mentioned that there may be a fault in the systemcomponent that has been subjected to a diagnostic procedure, inparticular a diagnostic procedure according to the sixth aspect of theinvention. Alternatively, the fault can also be caused by a deviatingsystem component, whereby the fault is transferred to the systembehaviour of the system component inferior to the diagnostic procedure,in particular by means of a transfer function.

According to a fourth category for a cause of a deviation between theactual system behaviour and the expected system behaviour, there is anunknown cause for the deviation of the system behaviour of a systemcomponent.

If no cause for the deviation between the actual system behaviour andthe expected system behaviour of the system component can be determinedon the basis of a diagnostic signal, there is an unknown cause.

It should be kept in mind, among other things, that so far there are notenough empirical values for a conceivable cause for the deviation or anassignment of a cause would lead to an ambiguous result.

A resolution strategy is a method which, when applied to a cleaningsystem of a motor vehicle, is designed to trace back a deviation betweenthe actual system behaviour and the expected system behaviour found in asystem component of a cleaning system of a motor vehicle.

In other words, a resolution strategy can advantageously achieve thatthe deviation with regard to the system component has become smaller orthat the actual system behaviour again corresponds to the expectedsystem behaviour.

Especially preferred, the resolution strategy exhibits an inputquantity, which influences the cleaning system and/or the systemcomponent on the cleaning system and/or the system component when theresolution strategy is applied.

Preferably a resolution strategy exhibits a notice to the driver of themotor vehicle and/or the manufacturer of the motor vehicle.

Preferably, a resolution strategy exhibits a measure to plan maintenanceand/or repair of the motor vehicle.

A resolution strategy is preferably based on experience with theoperation of a cleaning system. This experience may have been gainedduring the operation of the motor vehicle and/or in the laboratoryand/or on the basis of a numerical model and/or may be the result ofexisting maintenance recommendations and/or may be based on heuristicfindings.

A suitable resolution strategy depends on the deviation of the systembehaviour and/or the present diagnostic signal, especially on thepresent diagnostic signal determined according to the sixth aspect ofthe invention.

Preferably a suitable resolution strategy depends on a process quantity.

Preferably, a resolution strategy depends on the input quantity thataffected the cleaning system and/or the system component when thedeviation of the system behaviour and/or the diagnostic signal wasdetermined.

It can be advantageously achieved by a resolution strategy that a systemcomponent of a cleaning system behaves again as it is to be expected.This allows the functionality of a cleaning system to be returned toregular operation despite a previously existing deviation of the systembehaviour.

Overall, a resolution strategy can be so advantageous that thefunctionality of the driver assistance systems can be maintained longerdespite a diagnosed deviation of the system behaviour of a systemcomponent of the cleaning system.

Here it is specifically proposed to select a resolution strategysuitable for a present diagnostic signal from a list of known resolutionstrategies.

In particular, it is proposed that the list of known resolutionstrategies be taken from a database that can be accessed from the motorvehicle. The motor vehicle can also be wirelessly connected to asuitable database of exhibiting resolution strategies.

In addition to the resolution strategy, the database also exhibits theassociated diagnostic signal, which the resolution strategy has been setup to remedy.

In addition to the resolution strategy, the database preferably exhibitsthe input quantity which has an effect on the system component and/orthe cleaning system when determining the present diagnostic signal.

In addition to the resolution strategy, the database could preferablyexhibit the process quantity that influenced the system component and/orthe cleaning system in determining the present diagnostic signal.

Preferably, the resolution strategy can be determined by means of apresent diagnostic signal, especially by means of a present diagnosticsignal obtained according to the sixth aspect of the invention.

The resolution strategy is selected from the database whose diagnosticsignal assigned to it in the database best matches the presentdiagnostic signal.

Preferably, the most suitable resolution strategy is selected from thedatabase using the smallest Euclidean distance between the diagnosticsignal assigned to it in the database and the present diagnostic signal.

When determining the resolution strategy by means of the presentdiagnostic signal, particular preference is given to the input quantityand/or the process quantity which has an effect on the system componentand/or the cleaning system when determining the present diagnosticsignal.

It is furthermore preferably suggested, that the database with theresolution strategies is first prefiltered with regard to the bestfitting input quantity and/or the best fitting process quantity, inparticular on the basis of the corresponding Euclidean distance betweenthe input quantity and/or process quantity stored in the diagnosticsignal and the input quantity and/or process quantity in the database.

It is proposed to subsequently select the resolution strategy on thebasis of the present diagnostic signal according to the smallestpossible Euclidean distance to the remaining resolution strategiesaccording to the above procedure.

A resolution strategy can thus be advantageously selected which isadvantageously set up to reduce a deviation of the system behaviour of asystem component of the cleaning system and/or to inform the driverand/or the manufacturer of the fault and/or to bring about an upcomingmaintenance and/or repair measure.

Furthermore, it should be specifically considered that the empiricalvalues on which each resolution strategy is based are systematised tosuch an extent that they are valid or at least transferable for aplurality of different system components and/or a plurality of differentcleaning systems.

In this way, it can be advantageously achieved that on the basis ofexisting experience with different system components of differentcleaning systems, in particular different cleaning systems of differentmanufacturers or suppliers, an unambiguous assignment can be madebetween a present diagnostic signal and a resolution strategy, inparticular an unambiguous cross-manufacturer and cross-type assignmentfor the cleaning system and/or the specific system component.

A conceivable resolution strategy is that if there is a deviation of theactual system behaviour from the expected system behaviour in a cleaningfluid pump, which indicates a blockage of the flow channel between thecleaning fluid reservoir and an outlet opening at a nozzle, inparticular by the increased energy requirement of the cleaning fluidpump and/or by a comparatively low outlet quantity of cleaning fluid atan outlet opening of a nozzle and/or by an increased static pressure ofthe cleaning fluid downstream of the cleaning fluid pump and/or by alower flow velocity of the cleaning fluid downstream of the cleaningfluid pump, an increase in the supply voltage and/or the target speed ofthe cleaning fluid pump is proposed as the resolution strategy. This canbe advantageous in removing any blockage and flushing it out of thecleaning system.

If a cleaning fluid pump exhibits a high current flow but no impulsesfrom a present Hall sensor, this indicates a stalled motor of thecleaning fluid pump.

If no cleaning result is achieved, in particular a gain of availability,and/or if activation of a cleaning fluid pump cannot be observed, it issuggested to check the controller of the cleaning system, in particularthe electronic control unit of the cleaning system, for a phaseopen-circuit fault and/or a phase-ground fault and/or a short-circuitfault. If a fault is detected, the planning of a service and maintenancemeasure is suggested.

It is proposed to operate a cleaning fluid pump in case of a deviationbetween the actual system behaviour and the expected system behaviour atdifferent pressures and/or engine speeds. Since a cycle of differentpressures and/or engine speeds does not result in the actual systembehaviour again corresponding to the expected system behaviour, it isproposed to send a corresponding warning to the driver and/or themanufacturer of the motor vehicle and to signal that the cleaning fluidpump should be replaced and/or to cause the cleaning system to stopusing the cleaning fluid pump and/or the whole cleaning system until thecleaning fluid pump has been replaced.

If the outside temperature is above a defined temperature, especiallyabove 45° C., especially preferred above 55° C., and/or if the outsidetemperature is below a defined temperature, especially below 0° C.,especially preferred below minus 15° C., it is proposed not to operatethe cleaning fluid pump anymore, whereby the remaining life expectancyof the cleaning fluid pump can be advantageously increased.

With regard to a cleaning fluid pump, it is proposed to monitor the lifeexpectancy of the cleaning fluid pump, in particular by means ofmonitoring the flow velocity in conjunction with the cleaning fluid pumpand/or the static pressure in conjunction with the cleaning fluid pumpand/or the flow rate through the cleaning fluid pump and/or by means ofmonitoring the number of already existing operating cycles of thecleaning fluid pump and/or by means of monitoring the time of use of thecleaning fluid pump to date, and if it is foreseeable that the lifeexpectancy of the cleaning fluid pump is approaching its end, it isproposed to send a corresponding warning to the driver and/or themanufacturer of the motor vehicle and to signal that the cleaning fluidpump is to be replaced within the expected remaining life, and/or tocause the cleaning system to stop using the cleaning fluid pump and/orthe entire cleaning system until the cleaning fluid pump has beenreplaced.

If a cleaning fluid pump has an excessive energy requirement, which canbe detected in particular by a current sensor, it is proposed to warnthe driver and/or the manufacturer of the motor vehicle accordingly andto signal that the cleaning fluid pump is to be replaced and/or to causethe cleaning system to stop using the cleaning fluid pump and/or theentire cleaning system until the cleaning fluid pump has been replaced.

If a cleaning fluid pump has an excessive temperature, which can inparticular be detected with a temperature sensor, it is proposed to warnthe driver and/or the manufacturer of the motor vehicle accordingly andto signal that the cleaning fluid pump is to be replaced and/or to causethe cleaning system to stop using the cleaning fluid pump and/or theentire cleaning system until the cleaning fluid pump has been replaced.

With regard to a cleaning fluid pump, it is proposed to monitor theperformance of the pump, in particular by means of a deviation of theactual system behaviour from the expected system behaviour, inparticular preferably by means of a flow sensor in an operativeconnection to the cleaning fluid pump and/or by means of a pressuresensor flow sensor in an operative connection to the cleaning fluid pumpand/or a current meter flow sensor in an operative connection to thecleaning fluid pump. If a deviation occurs, it is proposed to warn thedriver and/or the manufacturer of the motor vehicle accordingly and tosignal that the cleaning fluid pump is to be replaced and/or to causethe cleaning system to stop using the cleaning fluid pump and/or theentire cleaning system until the cleaning fluid pump has been replaced.

In particular, it is proposed to monitor the system behaviour of acleaning fluid pump by means of a flow sensor in an active connection tothe cleaning fluid pump and/or by means of a pressure sensor flow sensorin an active connection to the cleaning fluid pump and/or a flow meterflow sensor in an active connection to the cleaning fluid pump. If thedeviation indicates that the cleaning fluid pump is stalled, especiallyin frozen condition, and/or that the cleaning fluid pump is blocked withdebris, it is suggested to switch off the cleaning fluid pump and towarn the driver and/or the manufacturer of the motor vehicle and tosignal that the cleaning fluid pump should be replaced.

A conceivable resolution strategy consists in the fact that in thepresence of a deviation of the actual system behaviour from the expectedsystem behaviour in a cleaning fluid reservoir, which indicates acleaning fluid reservoir split, in particular as a result of frost,and/or a cleaning fluid reservoir leak, in particular by an irregularlydecreasing static pressure in an operative connection with the bottom ofthe cleaning fluid reservoir and/or by an irregularly decreasing fillinglevel of the cleaning fluid reservoir determined by means of a levelsensor, a planning of a maintenance and/or repair measure is proposed asa resolution strategy. In this way, the cleaning system can be madeoperational again in an advantageous way.

With regard to a level sensor, in particular a level sensor which is inoperative connection with a cleaning fluid reservoir, it is proposed tomonitor the functionality and if it indicates that a functionality nolonger exists, in particular by no longer emitting a signal and/or ifthe emitted signal does not match the expected system behaviour, it isproposed to subject the level sensor to a maintenance measure and toreplace it if necessary.

If a level sensor has an excessive energy demand, which can be detectedwith a current sensor in particular, it is proposed to warn the driverand/or the manufacturer of the motor vehicle accordingly and to signalthat the level sensor should be replaced and/or to cause the cleaningsystem to stop using the cleaning fluid pump and/or the entire cleaningsystem until the level sensor has been replaced.

If a level sensor has an excessive temperature, which can in particularbe detected by a temperature sensor, it is proposed to warn the driverand/or the manufacturer of the motor vehicle accordingly and to signalthat the level sensor should be replaced and/or to cause the cleaningsystem to stop using the cleaning fluid pump and/or the whole cleaningsystem until the level sensor has been replaced.

A conceivable resolution strategy for a level sensor is to propose areplacement of the level sensor in case of an increased reaction time orsensing time.

A conceivable resolution strategy for a level sensor is to use a leakingthrough sensor, in particular at the interface to the cleaning fluidreservoir, particularly preferably at the interface between the cleaningfluid reservoir and the level sensor, to monitor whether there is anyleakage, in particular between the cleaning fluid reservoir and thelevel sensor, whereby a maintenance and/or repair measure is planned ifthere is a leak.

A conceivable resolution strategy consists in the fact that in thepresence of a deviation of the actual system behaviour from the expectedsystem behaviour in a cleaning fluid line, which indicates a blockage ofthe cleaning fluid line, in particular as a result of frost, and/or acleaning fluid line leak, in particular by an irregularly decreasingstatic pressure in an operative connection with the cleaning fluid lineand/or by a blockage in a cleaning fluid line determined by means of aflow gauge, planning of a maintenance and/or repair measure and/orheating of the cleaning fluid line is proposed as a resolution strategy.This is an advantageous way to make the cleaning system operationalagain.

With regard to a telescopic wash nozzle, it is proposed to monitor thelife expectancy of the telescopic wash nozzle, in particular bymonitoring the number of already existing operating cycles of thetelescopic wash nozzle, and if it is foreseeable that the lifeexpectancy of the telescopic wash nozzle is approaching its end, it isproposed to send a corresponding warning to the driver and/or themanufacturer of the motor vehicle and to signal that the telescopic washnozzle should be replaced within the expected remaining life expectancy.

Furthermore, with regard to a telescopic wash nozzle, it is proposed tomonitor the number of already existing operating cycles of thetelescopic wash nozzle and, if a predefined number of operating cyclesis reached, to send a warning to the driver and/or the manufacturer ofthe motor vehicle and signal that the telescopic wash nozzle should bechecked within the next 1000 operating cycles.

A possible resolution strategy for a heated wash nozzle is to suggestswitching off the heater for the wash nozzle if there is an increasedenergy demand.

A conceivable resolution strategy for a heated wash nozzle is to switchon the heater for the wash nozzle when there is a low temperature,especially a temperature above freezing and below.

It is proposed to review the system behaviour of a wash nozzle, inparticular with regard to cleaning performance, particularly preferredby means of a gain in availability, and to replace the wash nozzle ifthe actual system behaviour of the wash nozzle differs from the expectedsystem behaviour.

Furthermore, it is proposed to monitor the distribution of the spraypattern by means of the optical sensor, in particular whether the spraypattern covers the surface to be cleaned, and if a deviation occurs toplan a maintenance and/or repair measure for the wash nozzle.

It is proposed to monitor the heating of a wash nozzle by means of anoptical sensor, especially in a referenced area, and if a deviationoccurs to plan a maintenance and/or repair measure for the wash nozzle.

It is proposed to check the flow velocity in an active connection withthe wash nozzle and/or the pressure of the flow in an active connectionwith the wash nozzle and to replace the wash nozzle if a deviation isdetected.

In connection with a wash nozzle, it is proposed to check whether thewash nozzle is frozen and/or otherwise blocked by means of a flowvelocity of the cleaning fluid in an effective connection with the washnozzle and/or a pressure of the cleaning fluid in an effectiveconnection with the wash nozzle. If the wash nozzle is frozen, it issuggested to switch on the heater of the wash nozzle. If there is adifferent problem with the wash nozzle, it is suggested to send acorresponding warning to the driver and/or the manufacturer of the motorvehicle and to signal that the wash nozzle should be replaced.

For a wash nozzle, it is proposed to check the wash nozzle for anyleakage, in particular with a drip sensor, preferably by means of anoptical sensor, which checks whether the wash nozzle has dripping, inparticular if the cleaning fluid pump is switched off. If dripping isdetected on the wash nozzle, it is suggested to replace the wash nozzle.

With regard to a wash valve, it is proposed to monitor the lifeexpectancy of the wash valve, in particular by monitoring the number ofexisting operating cycles of the wash valve, and if it can be foreseenthat the life expectancy of the wash valve is approaching its end, it isproposed to send a corresponding warning to the driver and/or themanufacturer of the motor vehicle and to signal that the wash valveshould be replaced within the expected residual life.

Furthermore, with regard to a wash valve, it is proposed to monitor thenumber of already existing operating cycles of the wash valve and, if apredefined number of operating cycles is reached, to send acorresponding warning to the driver and/or the manufacturer of the motorvehicle and to signal that the wash valve should be checked within thenext 1000 operating cycles.

If a solenoid actuating a wash valve has an excessive energyrequirement, which can be measured with a current sensor in particular,it is proposed to warn the driver and/or the manufacturer of the motorvehicle accordingly and to signal that the wash valve is to be replacedand/or to cause the cleaning system to stop using the cleaning fluidpump and/or the entire cleaning system until the wash valve has beenreplaced.

If a solenoid actuating a wash valve has an excessive temperature, whichcan in particular be detected with a temperature sensor, it is proposedto warn the driver and/or the manufacturer of the motor vehicleaccordingly and to signal that the wash valve is to be replaced and/orto cause the cleaning system to stop using the cleaning fluid pumpand/or the entire cleaning system until the wash valve has beenreplaced.

With regard to a wash valve, it is proposed to monitor the flowconditions in an interaction with the wash valve, in particular thestatic pressure and/or the flow velocity downstream of the wash valve,and if the actual system behaviour differs from the expected systembehaviour, to plan a maintenance and/or repair measure.

Furthermore, for a wash valve it is proposed to check by means of aforce sensor and/or a distance gauge whether the solenoid is travellingsufficiently, and if the actual system behaviour deviates from theexpected system behaviour to plan a maintenance and/or repair measure.

With regard to a solenoid operated air valve, it is proposed to monitorthe life expectancy of the solenoid operated air valve, in particular bymonitoring the number of already existing operating cycles of thesolenoid operated air valve, and if it is foreseeable that the lifeexpectancy of the solenoid operated air valve is approaching its end, itis proposed to send a corresponding warning to the driver and/or themanufacturer of the motor vehicle and to signal that the solenoidoperated air valve is to be replaced within the expected residual life.

Furthermore, with regard to a solenoid operated air valve, it isproposed to monitor the number of already existing operating cycles ofthe solenoid operated air valve and, if a predefined number of operatingcycles is reached, to send a corresponding warning to the driver and/orthe manufacturer of the motor vehicle and to signal that the solenoidoperated air valve should be checked within the next 1000 operatingcycles.

If a solenoid actuating an air valve has an excessive energyrequirement, which can in particular be detected with a current sensor,it is proposed to warn the driver and/or the manufacturer of the motorvehicle accordingly and to signal that the air valve is to be replacedand/or to cause the cleaning system to stop using the cleaning fluidpump and/or the entire cleaning system until the air valve has beenreplaced.

If a solenoid actuating an air valve has an excessive temperature, whichcan in particular be detected by a temperature sensor, it is proposed towarn the driver and/or the manufacturer of the motor vehicle accordinglyand to signal that the air valve is to be replaced and/or to cause thecleaning system to stop using the cleaning fluid pump and/or the entirecleaning system until the air valve has been replaced.

A conceivable resolution strategy for a heated air nozzle is to suggestswitching off the heater for the air nozzle if there is an increasedenergy requirement.

A possible resolution strategy for a heated air nozzle is to switch onthe heater for the air nozzle when there is a low temperature,especially a temperature above freezing and below.

It is proposed to check the system behaviour of an air nozzle, inparticular with regard to cleaning performance, particularly preferredby means of a gain in availability, and to replace the air nozzle if theactual system behaviour of the wash nozzle deviates from the expectedsystem behaviour.

It is proposed to monitor the heating of an air nozzle by means of anoptical sensor, especially in a referenced area, and if a deviationoccurs to plan a maintenance and/or repair measure for the air nozzle.

It is proposed to check the flow velocity in an active connection withthe air nozzle and/or the pressure of the cleaning fluid flow in anactive connection with the air nozzle and to replace the air nozzle if adeviation is detected.

In connection with an air nozzle, it is proposed to check whether theair nozzle is frozen and/or otherwise blocked by means of a flowvelocity of the cleaning fluid in an effective connection with the airnozzle and/or a pressure of the cleaning fluid in an effectiveconnection with the air nozzle. If the air nozzle is frozen, it issuggested to switch on the heating of the air nozzle. If there is adeviating problem with the air nozzle, it is suggested to send acorresponding warning to the driver and/or the manufacturer of the motorvehicle and to signal that the air nozzle should be replaced.

When implementing a resolution strategy selected here, particularconsideration should be given to implementing the resolution strategyaccording to the eighth aspect of the invention.

If a selected and implemented resolution strategy is successful, then anactual system behaviour of the system component of the cleaning systemof a motor vehicle, which corresponds to the expected system behaviourfor this system component, is advantageous.

If an implementation of a resolution strategy chosen here, in particularan implementation of a resolution strategy according to the eighthaspect of the invention, does not lead to the success that the actualsystem behaviour again corresponds to the expected system behaviour andit can be assumed that the cause of the deviation is not a defect or anaging phenomenon, it is proposed to select a deviating resolutionstrategy, in particular the resolution strategy which fits best in eachcase, and to implement this newly selected resolution strategy, inparticular according to the eighth aspect of the invention.

It should be noted that the subject-matter of the seventh aspect can beadvantageously combined with the subject-matter of the preceding aspectsof the invention, either individually or cumulatively in anycombination.

According to an eighth aspect of the invention, the task is solved byusing of a selected resolution strategy, preferably a resolutionstrategy selected according to the seventh aspect of the invention, by

-   -   sending a signal to the driver and/or the manufacturer of the        motor vehicle, and/or    -   improve the system behavior by applying the selected resolution        strategy with the cleaning system, and/or    -   planning maintenance or repair of the cleaning system.

With regard to the implementation of a resolution strategy, inparticular a resolution strategy which has been selected according tothe seventh aspect of the invention, it is proposed to proceed dependingon the identified or at least suspected cause.

If the cause of a deviation between an actual system behaviour and anexpected system behaviour is unknown for a system component and ifconsequently no resolution strategy is known, it is proposed to send asignal to the driver of the motor vehicle and/or the manufacturer of themotor vehicle.

In this way, the driver can be warned advantageously of a possiblemalfunction of the cleaning system and thus possibly also of animpending malfunction of a driver assistance system.

It is also proposed that the signal to the manufacturer of the motorvehicle should preferably include a diagnostic signal, in particular adiagnostic signal according to the sixth aspect of the invention. Inaddition, it is proposed that the signal to the manufacturer of themotor vehicle preferably has a deviation and/or the actual outputquantity and/or the expected output quantity, preferably depending onthe associated input quantity and/or the associated process quantity, inparticular the above quantities according to the sixth aspect of theinvention.

In this way, the manufacturer of the motor vehicle can further expandhis experiences with a system component of a cleaning system and providea resolution strategy for this case, so that a fault of the same or atleast similar type can soon be remedied advantageously by means of asuitable resolution strategy.

If the cause of a deviation between an actual system behaviour and anexpected system behaviour for a system component is a fault, inparticular a fault for which a resolution strategy is known, inparticular a resolution strategy according to the seventh aspect of theinvention is known, the application of the resolution strategy isproposed, in particular the application of a resolution strategy withthe input quantity known to the resolution strategy.

In this way, the disturbance can be remedied in an advantageous way.

If an application of resolution strategy is not successful and there isstill a deviation between the actual system behaviour and the expectedsystem behaviour for the system component, it is proposed to select thenext best resolution strategy to remedy the disorder, especiallyaccording to the seventh aspect of the invention, and to apply thisresolution strategy. Alternatively, it is proposed to repeat theapplication of the selected resolution strategy or strategies.

If a failure cannot be resolved after multiple use of a selectedresolution strategy, it is proposed to reclassify the cause of thedeviation between the actual system behaviour and the expected systembehaviour as unknown and to proceed according to the above proposedcourse of action for unknown causes.

If the cause of a deviation between an actual system behaviour and anexpected system behaviour for a system component is an ageingphenomenon, it is proposed to determine a residual life for the affectedsystem component and to plan a maintenance operation to replace orrepair the affected system component within the residual life.

It is advantageous to repair or replace an aging system component,preferably without risking a failure of the cleaning system.

If the cause for a deviation between an actual system behaviour and anexpected system behaviour for a system component is a defect, it issuggested to have a defect repairable by untrained personnel repairableby a message to the driver of the motor vehicle by the driver of themotor vehicle. If the driver does not want to carry out this action orif it is not successful, the planning of a corresponding maintenanceaction is proposed.

If the cause for an untrained personnel cannot be rectified, theplanning of a maintenance task is proposed.

It is therefore advantageous to return the cleaning system to a fullyfunctional state.

It is proposed to use an adaptive learning approach when applying aresolution strategy where the system sends an error message to thedriver and/or the manufacturer of the motor vehicle if a surface to becleaned is not sufficiently cleaned after a number of attempts.

It is understood that the advantages of a resolution strategy,preferably a resolution strategy according to the seventh aspect of theinvention, as described above, directly extend to the use of aresolution strategy, preferably the use of a resolution strategyaccording to the eighth aspect of the invention.

It should be noted that the subject-matter of the eighth aspect can beadvantageously combined with the subject-matter of the preceding aspectsof the invention, either individually or cumulatively in anycombination.

According to a ninth aspect of the invention, the task is solved by amethod for indirectly deriving a systematic dependence for a systembehaviour of a soiling process of a surface of a motor vehicle,

-   -   wherein a sensor is operatively connected to the surface,    -   wherein a soiling condition of the surface can be evaluated by        means of an availability of the sensor,    -   wherein the soiling process is evaluated between a first        availability of the sensor and a second availability of the        sensor,    -   wherein the motor vehicle has travelled a distance travelled by        the motor vehicle between the first availability and the second        availability,    -   wherein the motor vehicle exhibits an increase in an operating        time by covering the distance travelled by the motor vehicle        between the first availability and the second availability,    -   wherein no cleaning process is performed between the first        availability and the second availability,    -   wherein the second availability is preferably less than the        first availability by a change of availability of the sensor due        to soiling of the surface,    -   whereby the change of availability depends on an input quantity        by means of the system behaviour of the soiling process,    -   exhibiting the following steps:        -   Determine the input quantity as a first parameter of the            method by means of at least one sensor;        -   Determine the change of availability as a second parameter            of the method by means of the sensor, wherein the change of            availability is calculated by the difference between the            second availability and the first availability;        -   Digitalize where necessary and record the determined first            and second parameters by a data processing system, whereby            the data processing system exhibits an electronic data            processing and evaluation system and a database;        -   Store the determined first and second parameters in an            ordered manner with reference to one another in the database            as a data set of a dependency table;        -   Derive the systematic dependence between the first and            second parameters by means of the electronic data processing            and evaluation system from at least two data sets of the            dependency table stored in the database, preferably from at            least 50 data sets of the dependency table, particularly            preferably from at least 200 data sets of the dependency            table, whereby the electronic data processing and evaluation            unit accesses the data sets of the dependency table and            determines the systematic dependence from the data sets of            the dependency table by means of an algorithm; and        -   Preferably store the derived systematic dependence in the            database and/or the electronic data processing and            evaluation unit and/or an electronic control unit.

Sensors installed on a motor vehicle, in particular optical sensors, arepredominantly protected by an external surface that can shield therespective sensor from the external environmental conditions and thusprotect it from any damaging influence from the external environmentalconditions.

In particular, it is conceivable that a windscreen or a rear window ofthe motor vehicle against the effects of external environmentalconditions could protect a sensor.

A surface shielding the sensor is often also part of the outer surfaceof the entire motor vehicle and is therefore also exposed to a soilingprocess due to the external environmental conditions. The deposited dirtcan impair the functionality of the sensor. This impairment can go sofar that a sensor can no longer provide information or the informationprovided is no longer reliable, so that it can no longer be used in theoriginal sense.

In this case, the soiling condition of a surface shielding a sensor isevaluated by means of an availability of the corresponding sensor. Highavailability values are to be interpreted in such a way that there is noor only minor contamination on the surface covering the sensor. Lowavailability values, on the other hand, are to be interpreted as anindicator of increased contamination.

In the case of a sensor that is operatively connected to a windshield ora rear window, the position of the sensor is often determined so thatthe part of the windshield or the rear window that is operativelyconnected to the sensor can be cleaned with a windshield wiper using acleaning fluid if necessary. However, all other positions of a sensorare also expressly conceivable, which can be cleaned using separatecleaning means if necessary.

The availability of a sensor can be advantageously increased if thesurface that is connected to a sensor and is already dirty is cleaned.

The dirt deposited on the surface of a motor vehicle is subject to acontamination process. A contamination process is subject to an inherentsystem behaviour.

The system behaviour of a soiling process depends on at least one inputparameter, whereby a plurality of input parameters is conceivable whichsignificantly influence the soiling process.

The number and selection of input parameters that significantlyinfluence the soiling process may depend in particular on the climaticconditions at the operating location of the motor vehicle. The climaticconditions can be understood as the season and/or the region in whichthe motor vehicle is operated on the planet.

If the system behaviour of the soiling process is known, it can be usedin particular to make a statement about the expected future availabilityof a sensor depending on the pre-planned and/or known future inputparameters. In particular, with the help of a corresponding systembehaviour and the pre-planned and/or known future input parameter, itcan be determined after which distance to be covered and/or after whichactive operating time still to be completed an availabilitycorresponding to a threshold of availability is expected to be reached.

This is precisely what can contribute to saving cleaning resources whenplanning a cleaning process, preferably when planning aresource-efficient cleaning process, in particular when planning aresource-efficient cleaning process after the third and/or fourth aspectof the invention, in particular while maintaining a cleaning mode in thesense of the fourth aspect of the invention.

Here a concrete method for indirectly deriving a systematic dependencefor a system behaviour of a soiling process of a surface of a motorvehicle is proposed, in which a soiling process between a firstavailability of the sensor and a second availability of the sensor isfirst evaluated and the empirical values collected are transferred intoa systematic dependence, which describes the system behaviour of asoiling process of a surface.

The first availability marks the starting point of the evaluationprocess, at which an empirical value regarding the system behaviour iscollected.

Among other things, it is conceivable that this starting point falls onthe starting time of the motor vehicle, i.e. the time at which therespective active use of the motor vehicle begins. Furthermore, it isconceivable that the starting point will fall at the point in time atwhich the motor vehicle begins to roll. It is also conceivable that thestarting time, i.e. the determination of the first availability, fallsat the time when the environmental conditions, in particular the weatherconditions, of the motor vehicle change.

The second availability marks the end time of the time window bydetermining an empirical value for the soiling process between the starttime and the end time.

In particular, this end time can coincide with the time at which theactive usage time of the motor vehicle ends, in particular with the timeat which the motor vehicle is parked. Furthermore, it is conceivablethat the end time may fall at the point in time at which the motorvehicle comes to a standstill. And it is also conceivable for the endtime to fall at the point in time at which the environmental conditions,in particular the weather conditions, change.

It should be expressly mentioned that a start time can also be assignedto a plurality of end times. Thus, among other things, a continuousobservation period is conceivable, which is characterized by a singlediscrete start time, to which several observation periods are assignedby allocation of several end times, so that a separate experience valuecan be collected for each end time.

Furthermore, it should be expressly pointed out that an observationperiod can also be characterized by a given time unit, so thatexperience values with different start times and different end times canbe collected continuously. Alternatively, it is conceivable that theseobservation periods also overlap.

It should also be expressly pointed out that empirical values on thesoiling behaviour of a surface can also result from observation periodswhich each have a different start time and a common end time.

All of the above variants for the observation of empirical values havein common that they include an active operation of the motor vehicle,i.e. a period of time in which the motor vehicle is at least designatedto cover a distance between the determination of the first and thesecond availability, whereby it is also conditional, as it were, thatthe active operating time of the motor vehicle has increased between thetime of the determination of the first availability and the time of thedetermination of the second availability.

It goes without saying that empirical values about the soiling behaviourof a surface are invalid if a cleaning process of the relevant surfacewas carried out between the determination of the first availability andthe second availability, since in this way the second availability wouldnot only be influenced by the pollution but also by the cleaningprocess. In other words, it is suggested that only empirical values areused to derive the systematic dependence, where no cleaning process wascarried out on the respective surface between the determination of thefirst availability and the determination of the second availability.

Thus, it should be considered that a second availability is determinedat the latest with the initiation or shortly before the initiation of acleaning process, at least at a time at which a cleaning process has notyet exerted any influence on the second availability.

Furthermore, it is specifically pointed out that through the influenceof environmental conditions the soiling condition and thus also theavailability of a surface can be improved, especially through theinfluence of rain and/or snowfall on the surface. Such a systematicinfluence on the soiling process shall also be considered separately,but can also be taken into account for the derivation of a systematicdependence with regard to a system behaviour of a soiling process,provided that the corresponding input quantity characterising theimprovement of availability is taken into account within the frameworkof the systematic dependence, in particular the amount of precipitationand/or the amount of snowfall. In this special case with considerationof the corresponding characterizing input quantity the firstavailability is smaller than the second availability.

The difference between the first availability and the secondavailability can therefore also be called a change of availability,which can be understood as a gain of availability or a loss ofavailability, depending on the case under consideration.

If between the time of the determination of the first availability andthe time of the determination of the second availability the same valueis determined for the availability of a surface in an active connectionwith a defined sensor, the data set can usually be discarded. This canbe justified by the fact that in the case that no change of theavailability takes place as a reaction to an input quantity, nounambiguous assignment of the recorded data to the system behaviour ofthe soiling process can be made.

There are exceptions in which a certain range of the input quantity isaccompanied by a certain gain in availability. This allows an equivalentloss of availability to be assigned to the deviating range of the inputquantity, so that the data set as a whole can be considered for thesystem behaviour of the soiling process.

This enables, among other things, that an expected precipitationquantity and/or an expected snowfall quantity can be taken into accountwith regard to the expected availability during the preliminary planningof a cleaning process. This can enable a further resource optimisationof the cleaning of a surface that is in an active connection with asensor, in particular within the framework of preliminary planningwithin the framework of the third and/or fourth aspect of the invention.

Furthermore, it should be pointed out that the discussed empiricalvalues about the soiling behaviour of a surface of a motor vehicle canbe derived not only from the active use of a motor vehicle but also fromthe laboratory and/or from a numerical model.

The following steps first serve to collect empirical values on thesystem behaviour of the soiling process, whereby the empirical valuesare first stored in a dependency table:

-   -   Determine the input quantity as a first parameter of the method        by means of at least one sensor;    -   Determine the change of availability as a second parameter of        the method by means of the sensor, wherein the change of        availability is calculated by the difference between the second        availability and the first availability;    -   Digitalize where necessary and record the determined first and        second parameters by a data processing system, whereby the data        processing system exhibits an electronic data processing and        evaluation system and a database;    -   Store the determined first and second parameters in an ordered        manner with reference to one another in the database as a data        set of a dependency table.

As soon as a sufficient number of empirical values or data sets isavailable, at least 50 data sets are preferred, especially at least 200data sets are preferred, the systematic dependence can be derived in thefollowing process step by means of an algorithm:

-   -   Derive the systematic dependence between the first and second        parameters by means of the electronic data processing and        evaluation system from at least two data sets of the dependency        table stored in the database, preferably from at least 50 data        sets of the dependency table, particularly preferably from at        least 200 data sets of the dependency table, whereby the        electronic data processing and evaluation unit accesses the data        sets of the dependency table and determines the systematic        dependence from the data sets of the dependency table by means        of an algorithm.

It should be pointed out that the above values for the number of datasets should not be understood as sharp limits, but rather should be ableto be exceeded or fallen below on an engineering scale without leavingthe described aspect of the invention. In simple terms, the values areintended to provide an indication of the size of the number of data setsproposed here.

It is expressly pointed out that the data sets necessary for derivingthe systematic dependence can also be loaded from a database containingcorresponding data sets before deriving the systematic dependence.

Preferably it should also be considered to store the derived systematicdependence, in particular in the database and/or the electronic dataprocessing and evaluation unit and/or an electronic control unit.

The systematic dependence derived from this ninth aspect of theinvention describes in an advantageous way the soiling process of asurface, especially of a surface which is in an active connection to asensor. The resulting systematic dependence can be used advantageouslyin the resource-optimal planning of a cleaning process, especially inthe pre-planning of a cleaning process according to the third and/orfourth aspect of the invention.

Preferably, the input quantity exhibits the distance travelled by themotor vehicle between the first availability and the secondavailability.

Here it is suggested that the input quantity exhibits the distance thatis covered by the motor vehicle between the determination of the firstavailability and the second availability.

In particular, a soiling process should be considered in which a sprayof water and/or dirt hits and deposits on the surface in active contactwith the sensor while the distance is being covered. If this type ofsoiling is stimulated by the active use of the vehicle, the relatedsoiling process may depend on the distance travelled. Now that it isproposed here to consider the distance as input quantity, thisinfluencing quantity can be advantageously taken into account whendetermining the systematic dependence.

Optionally, the input quantity exhibits the increase in the operatingtime by covering the distance travelled by the motor vehicle between thefirst availability and the second availability.

The contamination of a surface of a motor vehicle can depend on theoperating time. In particular, a form of contamination should beconsidered, in which dirt particles transported by the air are depositedon the respective surface.

As a consequence of the suggestion made here to consider the operatingtime as input quantity, it can be advantageously achieved that theoperating time can also be considered as influencing factor of thesoiling process.

Expediently, the input quantity exhibits a driving speed of the motorvehicle, preferably a course of the driving speed along the routebetween the first availability and the second availability.

The driving speed of a motor vehicle can also influence the soiling of asurface of the motor vehicle. In particular, the deposition of residuesof insects, which collide with the surface of the motor vehicle whiledriving with the motor vehicle, could be considered. In particular,insects are more likely to be able to evade the vehicle at a lower speedor to be guided around the vehicle by the air flow surrounding thevehicle. It is conceivable that insects or other microorganisms are morelikely to collide with the vehicle at increasing vehicle speeds than atslow speeds.

The proposal presented here to use the driving speed as input quantitycan also be advantageous for the systematic dependence derived with themethod, since it could then take the driving speed into account.

In a preferred embodiment, the input quantity exhibits a processquantity, preferably a humidity, particularly preferably a course of thehumidity along the route between the first availability and the secondavailability, and/or a temperature in the vicinity of the motor vehicle,particularly preferably a course of the temperature along the routebetween the first availability and the second availability, and/or arainfall, particularly preferably a course of the rainfall along theroute between the first availability and the second availability, and/ora snowfall quantity, particularly preferably a course of the snowfallquantity along the route between the first availability and the secondavailability.

A multitude of different process quantities can influence the soilingprocess and so it is suggested to consider at least one process quantityas input quantity. In particular, it is suggested to consider humidity,temperature, rainfall, snow and/or the like as input quantity.

Furthermore, it is conceivable to consider the process quantity by meansof different values along sections of the route of the motor vehicle, sothat it is advantageously possible for the process quantity to changeduring the route. This can also be accompanied by a change in processquantity, especially humidity, temperature, rainfall and/or snowfall,along the route within the framework of systematic dependence.

In an optional embodiment, the input quantity exhibits a vehicle type.

The vehicle type provides information about the characteristics of themotor vehicle in detail, in particular the type and quantity of sensorsinstalled, the placement of the sensors, the geometry and the positionof the surfaces that are operatively connected to the individualsensors, as well as the overall geometry of the vehicle, whichinfluences the flow around the motor vehicle and thus indirectly alsothe soiling process.

The at least one influencing variable related to the vehicle type shallbe considered as input quantity, whereby also the systematic dependencederived from empirical values can advantageously show a dependence tothe at least one influencing variable related to the vehicle type.

Preferably, the input quantity exhibits a current coordinate of themotor vehicle, preferably the coordinate of the motor vehicle along theroute between the first availability and the second availability.

Among other things, the current coordinate over which a vehicle willmove during active use can also have an influence on the soilingprocess.

In particular, the soiling process can be influenced by changing roadsurfaces which are dependent on the current coordinate of the vehicle.

Furthermore, different vegetation forms changing with the coordinate arethought of, whereby some vegetation forms are accompanied in particularwith a higher occurrence of insects and the like.

Thus, the current coordinate can also provide information about the typeand manner of pollution. A motor vehicle which is moved over a roadwaycovered with ice and snow pollutes in particular differently to a motorvehicle which is moved over a sandy and/or dusty roadway and differentlyto a motor vehicle which is moved over a rain-wet roadway.

It can thus be advantageously achieved in such a way that theinfluencing variables in an effective connection with a currentcoordinate over which a motor vehicle is moved can also be taken intoaccount for systematic dependence and thus indirectly also for thedesignated use of the systematic dependence.

Expediently, the input quantity exhibits the first availability of thesensor.

In particular, it should be considered here that a contamination statein a soiling process may not behave linearly to its influencingvariable. In this respect, the initial state can then also be decisivefor the development of the contamination state, whereby the initialstate can be evaluated with the first availability.

In particular, this way, on the one hand, an initial state ofcontamination of the surface and, on the other hand, an absolute changein availability between the times of first availability and secondavailability can be taken into account.

In this respect, it is concretely proposed here, among other things, toconsider the initial state of contamination of the surface as inputquantity. As a consequence, it can be advantageously achieved that themapping accuracy of the systematic dependence can be improved,especially with regard to nonlinearly developing contamination states ina soiling process.

Optionally, the systematic dependence is determined by means of aregression analysis.

Here it is suggested to use a regression algorithm as algorithm for theindirect derivation of a systematic dependence.

An algorithm which has already been tested in a large number ofapplications and which can be optimally selected and/or adaptedaccording to the system behaviour considered here can thus beadvantageously applied so that a systematic dependence of high qualitycan be determined.

Preferably, the systematic dependence is determined in form of a curve,preferably a curve and a coefficient of determination of the curve.

The advantage of this is that the systematic dependence is indicated bya curve as a function of at least one input quantity of the soilingprocess; in particular, this curve has no gaps, so that a clearassignment between an input quantity and a difference in availabilitydue to soiling can be achieved, in particular a continuous anddifferentiable dependency between an input quantity and a difference inavailability due to soiling, so that the systematic dependency isideally adapted for any mathematical methods for the use of the same.

The evaluation of a coefficient of determination from the determineddata and the curve determined by means of a regression model provides anindication for the precision of the systematic dependence, assuming thata sufficient number of data sets is available. It can be advantageouslyevaluated how meaningful a correlation between an input quantity of thesoiling process and a difference in availability due to soiling is andhow well existing or recorded data can be reproduced. In addition, inthe case of a large coefficient of determination, the curve also allowsstatements to be made about the margins of existing data. It isconceivable, for example, that data can be supplemented numericallyand/or extrapolated at the margins of existing data.

In an expedient embodiment, the systematic dependence is determined bymeans of an optimization process.

Here it is suggested that the parameters of a systematic dependence aredetermined by means of an optimization procedure, especially by means ofa minimization procedure, which minimizes the cumulated deviation of theempirical values considered by data sets from the systematic dependence.In this way, it is advantageously possible to determine a systematicdependence which can be derived in an optimal way, in particular with aminimum cumulated deviation from the initial experience values.

Preferably, the parameters of the systematic dependence are determinedby maximizing the resulting coefficient of determination.

Preferably, the systematic dependence is determined by means of aself-learning optimization method.

Among other things, it is proposed to use an algorithm that exhibits thecharacteristics of an algorithm from the class of machine learning.Thus, the algorithm is able to derive a systematic dependence betweenthe input quantity and a difference in availability due to soiling.

The advantage of this is that the complex task of indirectly deriving asystematic dependence by using self-learning optimization methods doesnot have to be laboriously adapted by humans to new conditions. Thus,time and money can be saved in the indirect derivation of systematicdependence.

The quality of the derived systematic dependence can be improved by theaspect proposed here, since an optimization procedure endeavors todetermine the optimal systematic dependence even in a multi-criteriaenvironment and under a variety of boundary conditions.

In this way, it is also conceivable that an optimization can be carriedout under a plurality of equal objectives and/or boundary conditions(multi criteria optimization). In particular, a class of algorithms isconsidered which can determine a Paretooptimum and/or a Paretofront. Inparticular, a class of algorithms in the area of simplex methods and/orevolutionary strategies and/or evolutionary optimization algorithmsand/or the like are suggested here for deriving the systematicdependence.

In an optional embodiment, the systematic dependence is derived usingdata sets of the dependency table from an already existing database,preferably data sets of an already existing database are accessedpreviously.

The advantage of this is that data from an existing database can also beused to derive the systematic dependence. Thus, it can be achieved thatempirical values do not have to be collected at a specific motor vehiclefirst and transferred into data of a database and later into asystematic dependence. In this way, existing data and empirical valuescan be used to derive a systematic dependence on the soiling processwithout first having to collect empirical values representing thesystematic dependence of the soiling process.

In an expedient embodiment, the already existing database iscontinuously expanded.

Advantageously, it can be achieved that the number of derivablesystematic dependencies increases over time.

Furthermore, it can be advantageously achieved that the accuracy of asystematic dependence can increase due to the larger number of empiricalvalues known by means of data sets.

Preferably, a new data set replaces the data set in the dependency tablewhich deviates most from the derived systematic dependence.

In particular, the fact that the experience value is exchanged with thelargest Euclidean distance to systematic dependence should be taken intoaccount.

Advantageously, it can be achieved that the systematic dependencebecomes more and more precise over time, which can be expressed by anincrease in the coefficient of determination.

Furthermore, this can have the advantage that even weakly correlatingsystematic dependencies can be better identified over time.

It should be noted that the subject-matter of the ninth aspect can beadvantageously combined with the subject-matter of the preceding aspectsof the invention, either individually or cumulatively in anycombination.

According to a tenth aspect of the invention, the task is solved by ause of

-   -   a dependency table exhibiting at least two data sets, preferably        exhibiting at least 50 data sets, particularly preferably        exhibiting at least 200 data sets,    -   wherein each data set exhibits at least one input quantity of        the soiling process, in particular the distance travelled by the        motor vehicle between the first availability and the second        availability and/or the operating time by covering the distance        travelled by the motor vehicle between the first availability        and the second availability, and/or a driving speed of the motor        vehicle, preferably a course of the driving speed along the        route between the first availability and the second        availability, and/or a process quantity, preferably a humidity,        particularly preferably a course of the humidity along the route        between the first availability and the second availability,        and/or a temperature in the vicinity of the motor vehicle,        particularly preferably a course of the temperature along the        route between the first availability and the second        availability, and/or a rainfall, particularly preferably a        course of the rainfall along the route between the first        availability and the second availability, and/or a snowfall        quantity, particularly preferably a course of the snowfall        quantity along the route between the first availability and the        second availability, and/or a vehicle type and/or a coordinate        of the motor vehicle, preferably the coordinate of the motor        vehicle along the route between the first availability and the        second availability, and/or the first availability of the        sensor, and the evaluated change of availability, stored in an        ordered manner with reference to one another,    -   and/or    -   a systematic dependence for a system behaviour of a soiling        process of a surface of a motor vehicle, preferably derived by a        method for indirectly deriving a systematic dependence according        to one of the claims 1 to 14, for a resource efficient cleaning,        preferably resource-saving cleaning, of at least one surface of        a motor vehicle,        to determine an expected availability at a distance or an        operating time of the motor vehicle yet to be covered by    -   insertion of the input quantity into the systematic dependence,        in particular the distance or the operating time of the motor        vehicle yet to be covered, and dissolution according to the        expected availability starting from an actual availability,    -   or    -   selection of the data set from the dependency table that best        matches the input quantity, in particular the distance or the        operating time of the motor vehicle yet to be covered, and        determination of the expected availability starting from the        actual availability,    -   or    -   means of linear interpolation between the adjacent data sets of        the dependency table that best match the input quantity, in        particular the distance or the operating time of the motor        vehicle yet to be covered, and determination of the expected        availability starting from the actual availability.

In accordance with this tenth aspect of the invention, it is nowproposed to use a dependency table, in particular a dependency tablewhich was created with the first steps of the procedure according to theninth aspect of the invention, and/or a systematic dependency, inparticular a systematic dependency derived according to the ninth aspectof the invention, for the determination of an expected availabilitydepending on a distance still to be covered by the motor vehicle or anoperating time still to be driven.

Whereby the dependency table exhibits at least one input quantity of thesoiling process, in particular at least one input quantity according tothe ninth aspect of the invention. In particular, it is conceivable,among other things, that the dependency table may exhibit at least thedistance travelled by the motor vehicle between the first availabilityand the second availability and/or the operating time by covering thedistance travelled by the motor vehicle between the first availabilityand the second availability and/or a driving speed of the motor vehicle,preferably a course of the driving speed along the route between thefirst availability and the second availability, and/or a processquantity, preferably a humidity, particularly preferably a course of thehumidity along the route between the first availability and the secondavailability, and/or a temperature in the vicinity of the motor vehicle,particularly preferably a course of the temperature along the routebetween the first availability and the second availability, and/or arainfall, particularly preferably a course of the rainfall along theroute between the first availability and the second availability, and/ora snowfall quantity, particularly preferably a course of the snowfallquantity along the route between the first availability and the secondavailability, and/or a vehicle type and/or a coordinate of the motorvehicle, preferably the coordinate of the motor vehicle along the routebetween the first availability and the second availability, and/or thefirst availability of the sensor, and the evaluated change ofavailability. It should preferably be considered that the dependencytable shows the input quantity and the evaluated change of availabilityin an ordered way to each other.

When using the systematic dependence proposed here for use to determinean expected availability of the sensor, a systematic dependence whichexhibits at least one input quantity according to the systematicdependence derived with the ninth aspect of the invention could inparticular be considered.

The method proposed here results in an expected availability for eachindividual sensor considered and must be repeated for evaluating theexpected availability for another sensor. It should be noted that asystematic dependence and/or a dependency table is only valid for morethan one sensor in exceptional cases, so that as a rule a differentdependency table and/or a different systematic dependence must be usedto determine the actual availability for each sensor.

Under real conditions, this often results in a different expectedavailability for each sensor considered, which can partly be explainedby the different soiling status and the deviating system behaviour ofthe respective soiling process.

The procedure proposed here can be described in particular by thefollowing variants of characterizing procedure steps:

According to a first variant it is suggested here that the inputquantity is used in the systematic dependence. In particular, it isproposed to insert the selected distance or the operating time of themotor vehicle yet to be covered into the systematic dependency,resulting in the expected change of availability as the function valueof the systematic dependence.

Furthermore, it is proposed to additionally determine the actualavailability. The sum of the expected change of availability and theactual availability gives the target value of the procedure, namely theexpected availability for the respective sensor for the selecteddistance or operating time of the motor vehicle yet to be covered.

According to a second variant of the procedure it is proposed to selecta data set with empirical values from the dependency table, which fitsbest to the input quantity with the selected distance or operating timeof the motor vehicle yet to be covered. In particular, it should beconsidered to select the best matching data set over the smallestEuclidean distance of all data sets of the dependency table between thedata set under consideration and the input quantity.

The data set selected from the dependency table contains an expectedchange of availability corresponding to the input quantity. The expectedavailability for the selected distance or operating time of the motorvehicle yet to be covered is the sum of the actual availability to bedetermined with the expected change of availability according to theselected data set of the dependency table associated with the sensor.

According to a third variant, two data sets are selected from thedependency table whose Euclidean distance to the selected input quantityis smallest. In this case, the expected change of availability isdetermined by linear interpolation, whereby the equalization line issupported by the two data points of the data sets. Here it isconceivable that the selected input quantity lies between the twoselected data points or on one side of the two selected data points.

Also according to this third variant, the expected availability resultsfrom the sum of the expected change of availability and the actualavailability to be determined.

It goes without saying that here the determination of the change ofavailability as a function of the selected distance or operating time ofthe motor vehicle yet to be covered is also explicitly suggested bymeans of a regression curve over a plurality of selected data sets fromthe dependency table, especially by means of a systematic dependence,especially by means of a systematic dependence according to the ninthaspect of the invention.

It should be expressly pointed out that the actual availability issupplied by the sensor or can otherwise be derived from the dataprovided by the corresponding sensor.

This makes it advantageously possible to determine an expected value forthe development of the availability in the future, in particulardepending on the distance still to be covered by the motor vehicle orthe operating time still to be driven.

After it had already been described in the third and fourth aspects ofthe invention that a resource-optimal cleaning process with regard tothe consumption of cleaning resources often does not start immediatelyat the time of the decision about the cleaning process, but shouldrather only be carried out in the future, preferably depending on theoccurrence of a defined soiling state, the planning of the availabilitycharacterising the soiling state is an advantageous possibility for theplanning of a resource-optimal cleaning process.

Furthermore, by the determination of an expected value of anavailability, a statement about the expected value of the remainingrange of the motor vehicle with the available cleaning resources can bemade advantageously.

This also enables a planning of the necessary cleaning mode according tothe fourth aspect of the invention, with which the pre-planned route canstill be managed with the existing cleaning resources without amaintenance stop becoming necessary to replenish cleaning resources.

The navigation system, depending on the expected range of the vehiclewith regard to the cleaning resources, in particular evaluated with thetenth aspect of the invention proposed here, can plan an optimalmaintenance stop to replenish cleaning resources on the pre-plannedroute, in particular a maintenance stop where the planned time overtarget deviates as little as possible from the time over target withoutmaintenance stop, taking into account a corresponding maintenance stop.

The operating time that can be determined here, among other things, canbe of particular interest to professional drivers. In particular, theoperation of a taxi should be considered, which is in active use until acertain time of day and during this time should make as many journeys aspossible and as few maintenance stops as possible. In this respect, astatement with a possible remaining operating time for this type ofmotor vehicle operation may be more relevant than a statement linked toa distance that can still be covered.

It should be pointed out that the above values for the number of datasets should not be understood as sharp limits, but rather should be ableto be exceeded or fallen below on an engineering scale without leavingthe described aspect of the invention. In simple terms, the values areintended to provide an indication of the size of the number of data setsproposed here.

It goes without saying that the advantages of systematic dependence, inparticular systematic dependence according to the ninth aspect of theinvention, also apply to the use of systematic dependence, in particularthe use of systematic dependence proposed here according to the tenthaspect of the invention.

It should be noted that the subject-matter of the tenth aspect can beadvantageously combined with the subject-matter of the preceding aspectsof the invention, either individually or cumulatively in anycombination.

According to an eleventh aspect of the invention, the task is solved bya use of

-   -   a dependency table exhibiting at least two data sets, preferably        exhibiting at least 50 data sets, particularly preferably        exhibiting at least 200 data sets,    -   wherein each data set exhibits at least one input quantity of        the soiling process, in particular the distance travelled by the        motor vehicle between the first availability and the second        availability and/or the operating time by covering the distance        travelled by the motor vehicle between the first availability        and the second availability, and/or a driving speed of the motor        vehicle, preferably a course of the driving speed along the        route between the first availability and the second        availability, and/or a process quantity, preferably a humidity,        particularly preferably a course of the humidity along the route        between the first availability and the second availability,        and/or a temperature in the vicinity of the motor vehicle,        particularly preferably a course of the temperature along the        route between the first availability and the second        availability, and/or a rainfall, particularly preferably a        course of the rainfall along the route between the first        availability and the second availability, and/or a snowfall        quantity, particularly preferably a course of the snowfall        quantity along the route between the first availability and the        second availability, and/or a vehicle type and/or a coordinate        of the motor vehicle, preferably the coordinate of the motor        vehicle along the route between the first availability and the        second availability, and/or the first availability of the        sensor, and the evaluated change of availability, stored in an        ordered manner with reference to one another,    -   and/or    -   a systematic dependence for a system behaviour of a soiling        process of a surface of a motor vehicle, preferably derived by a        method for indirectly deriving a systematic dependence according        to one of the claims 1 to 14, for a resource efficient cleaning,        preferably resource-saving cleaning, of at least one surface of        a motor vehicle,        to determine an expected distance or an expected operating time        of the motor vehicle yet to be covered when reaching a threshold        of availability by    -   calculation of the intersection between the threshold of        availability and the systematic dependence as a function of the        input quantity and derivation of the expected distance or the        operating time of the motor vehicle yet to be covered when        reaching the threshold of availability starting from the actual        availability,    -   or    -   selection of the data set from the dependency table that best        matches the threshold of availability starting from the actual        availability and determination of the expected distance or the        operating time of the motor vehicle yet to be covered when        reaching the threshold of availability,    -   or    -   means of linear interpolation between the adjacent data sets of        the dependency table that best match the threshold of        availability starting from the actual availability and        determination of the expected distance or the operating time of        the motor vehicle yet to be covered when reaching the threshold        of availability.

While the tenth aspect of the invention consists of determining anexpected availability for a selected distance or operating time of themotor vehicle yet to be covered, here an expected distance or operatingtime is to be determined until the expected availability reaches athreshold of availability.

In this context, a threshold of availability can be understood as atarget value for expected availability, in particular to indirectlydetermine an event upon whose occurrence a cleaning process is to bestarted, whereby the distance or operating time of the motor vehicle yetto be covered can be determined directly until the event is reached.

Furthermore, a threshold of availability can also be understoodliterally as a limit value for the availability, which should not befallen below. In this case, a safety margin can be planned to prevent athreshold of availability from being exceeded.

In accordance with this eleventh aspect of the invention, it is proposedhere to use a dependency table, in particular a dependency table whichwas created with the first steps of the procedure according to the ninthaspect of the invention, and/or a systematic dependency, in particular asystematic dependency derived according to the ninth aspect of theinvention, for the determination of an expected distance and/or anexpected operating time, whereby the expected availability as adependency of the expected distance and/or the expected operating timeshould then correspond to a threshold of availability.

With regard to the dependency table and/or the systematic distance, whathas already been done under the tenth aspect to the dependency tableand/or the systematic distance applies with the necessary adjustments.

Whereby the dependency table exhibits at least one input quantity of thesoiling process, in particular at least one input quantity according tothe ninth aspect of the invention. In particular, it is conceivable,among other things, that the dependency table may exhibit at least thedistance travelled by the motor vehicle between the first availabilityand the second availability and/or the operating time by covering thedistance travelled by the motor vehicle between the first availabilityand the second availability and/or a driving speed of the motor vehicle,preferably a course of the driving speed along the route between thefirst availability and the second availability, and/or a processquantity, preferably a humidity, particularly preferably a course of thehumidity along the route between the first availability and the secondavailability, and/or a temperature in the vicinity of the motor vehicle,particularly preferably a course of the temperature along the routebetween the first availability and the second availability, and/or arainfall, particularly preferably a course of the rainfall along theroute between the first availability and the second availability, and/ora snowfall quantity, particularly preferably a course of the snowfallquantity along the route between the first availability and the secondavailability, and/or a vehicle type and/or a coordinate of the motorvehicle, preferably the coordinate of the motor vehicle along the routebetween the first availability and the second availability, and/or thefirst availability of the sensor, and the evaluated change ofavailability. It should preferably be considered that the dependencytable shows the input quantity and the evaluated change of availabilityin an ordered way to each other.

When using the systematic dependence proposed here for use to determinean expected availability of the sensor, a systematic dependence whichexhibits at least one input quantity according to the systematicdependence derived with the ninth aspect of the invention could inparticular be considered.

The method proposed here provides an expected distance and/or anexpected operating time until the expected achievement of a threshold ofavailability for each sensor considered individually and must berepeated to achieve an expected distance and/or an expected operatingtime for another sensor.

It should be noted that a systematic dependence and/or a dependencytable is only valid for more than one sensor in exceptional cases, sothat as a rule a different dependency table and/or a differentsystematic dependence must be used to determine the actual availabilityfor each sensor.

Under real conditions this often results in a deviating expecteddistance and/or a deviating expected operating time for each consideredsensor, which can partly be explained by the deviating soiling statusand the deviating system behaviour of the respective soiling process.

The procedure proposed here can be described in particular by thefollowing variants of characterizing procedural steps:

According to a first variant, it is proposed here to calculate thepermitted change of availability on the basis of the actual availabilityto be determined first and the selected threshold of availability bymeans of difference formation between the actual availability and theselected threshold of availability.

Furthermore, it is proposed to insert the known range of the inputquantity into the systematic dependence associated with the sensor andto vary the range of the input quantity concerning the distance and/orthe operating time in such a way that the function value of thesystematic dependence indicates the permitted change of availability.The corresponding value for the distance and/or operating time thusobtained then corresponds to the expected distance and/or expectedoperating time until the selected threshold of availability is expectedto be reached.

In particular, a fixed point iteration procedure can be applied for thevariation of the distance and/or the operating time to achieve thepermitted change of availability. By contrast, the expected distanceand/or the expected operating time can also be calculated directly byresolving the systematic dependence with its function value, inparticular the permitted change of availability, according to thedistance and/or the operating time. The result of the equation thusobtained then corresponds to the expected distance and/or the expectedoperating time until the selected threshold of availability is expectedto be reached.

According to a second variant of the method it is also proposed tocalculate the allowed change of availability based on the data sets ofthe dependency table, whereby the actual availability is to bedetermined first and the allowed change of availability is to bedetermined by means of difference formation between the actualavailability and the selected threshold of availability.

Furthermore, it is proposed to select a data set with empirical valuesfrom the dependency table whose expected change of availability bestmatches the allowed change of availability, preferably by taking intoaccount those data sets which best match the already known range of theinput quantity.

In particular, the best matching data set could be selected over thesmallest euclidean distance of all data sets of the dependency tablebetween the expected change of availability corresponding to the dataset and the allowed change of availability.

The data set selected from the dependency table then contains theexpected distance and/or the expected operating time, especially theexpected distance and/or the expected operating time until the expectedthreshold of availability is reached.

According to a third variant, two data sets are selected from thedependency table whose euclidean distance between the expected change ofavailability and the allowed change of availability is smallest,preferably by taking into account those data sets which best fit thealready known range of the input quantity.

In this case, the expected distance and/or the expected operating timeuntil the expected threshold of availability is reached is determined bylinear interpolation, whereby the equalization line is supported by thetwo data points of the data sets. Here, among other things, it isconceivable that the input quantity to be selected lies between the twoselected data points or on one side of the two selected data points.

Also according to this third variant, the permitted change ofavailability results from the difference between the actual availabilityand the selected threshold of availability.

It goes without saying that here the determination of the expecteddistance and/or the expected operating time until the expected thresholdof availability is reached is explicitly suggested by means of aregression curve over a number of selected data sets from the dependencytable, in particular by a systematic dependence, in particular by asystematic dependence according to the ninth aspect of the invention.

It should be expressly noted that actual availability is supplied by thesensor or otherwise derived from the data provided by the correspondingsensor.

This makes it advantageously possible to determine an expected distancethat can still be covered by the vehicle until a threshold ofavailability is reached for a sensor.

After it had already been described in the third and fourth aspects ofthe invention that a resource-optimal cleaning process with regard tothe consumption of cleaning resources often does not start immediatelyat the time of the decision about the cleaning process, but shouldrather only be carried out in the future, preferably depending on theoccurrence of a defined state, the planning of the availabilitycharacterizing the soiling state is an advantageous possibility for theplanning of a resource-optimal cleaning process.

In this case, it is particularly important to remember that a surfaceconnected to a sensor is not cleaned until a threshold of availabilityis reached for the sensor. Thus, using this eleventh aspect of theinvention, it is advantageous to determine a distance or an activeoperating time for the vehicle that the vehicle can, as expected, coveruntil the surface needs to be cleaned or until it is preplanned to becleaned.

This enables a more precise planning of a cleaning process for a surfaceas well as an optimal planning of a cleaning process, especially after athird aspect of the invention.

Furthermore, with this eleventh aspect of the invention, it isadvantageously possible to plan a cleaning strategy with optimumcleaning resources, in particular to determine a cleaning strategyaccording to the fourth aspect of the invention.

Furthermore, it should be specifically considered that information thatcan be determined with the method proposed here can also be used byother systems of a motor vehicle in an advantageous manner, inparticular by a navigation system, which plans the route also dependingon the optimum cleaning strategy and a necessary maintenance stop forreplenishing cleaning resources that may be connected with it, wherebythe remaining range is decisive, which can still be achieved with theavailable resources and taking into account the fact that no sensor withits individual availability should fall under an individual threshold ofavailability.

The operating time that can be determined here, among other things, canbe of particular interest to professional drivers. In particular, theoperation of a taxi should be considered, which is in active use until acertain time of day and during this time should make as many journeys aspossible and as few maintenance stops as possible. In this respect, astatement with a possible remaining operating time for this type ofmotor vehicle operation may be more relevant than a statement linked toa distance that can still be covered.

It should be pointed out that the above values for the number of datasets should not be understood as sharp limits, but rather should be ableto be exceeded or fallen below on an engineering scale without leavingthe described aspect of the invention. In simple terms, the values areintended to provide an indication of the size of the number of data setsproposed here.

It goes without saying that the advantages of systematic dependence, inparticular systematic dependence according to the ninth aspect of theinvention, also apply to the use of systematic dependence, in particularthe use of systematic dependence proposed here according to the eleventhaspect of the invention.

It should be noted that the subject-matter of the eleventh aspect can beadvantageously combined with the subject-matter of the preceding aspectsof the invention, either individually or cumulatively in anycombination.

According to a twelfth aspect of the invention, the task is solved by ause of

-   -   a dependency table exhibiting at least two data sets, preferably        exhibiting at least 50 data sets, particularly preferably        exhibiting at least 200 data sets,    -   wherein each data set exhibits at least one input quantity of        the soiling process, in particular the distance travelled by the        motor vehicle between the first availability and the second        availability and/or the operating time by covering the distance        travelled by the motor vehicle between the first availability        and the second availability, and/or a driving speed of the motor        vehicle, preferably a course of the driving speed along the        route between the first availability and the second        availability, and/or a process quantity, preferably a humidity,        particularly preferably a course of the humidity along the route        between the first availability and the second availability,        and/or a temperature in the vicinity of the motor vehicle,        particularly preferably a course of the temperature along the        route between the first availability and the second        availability, and/or a rainfall, particularly preferably a        course of the rainfall along the route between the first        availability and the second availability, and/or a snowfall        quantity, particularly preferably a course of the snowfall        quantity along the route between the first availability and the        second availability, and/or a vehicle type and/or a coordinate        of the motor vehicle, preferably the coordinate of the motor        vehicle along the route between the first availability and the        second availability, and/or the first availability of the        sensor, and the evaluated change of availability, stored in an        ordered manner with reference to one another,    -   and/or    -   a systematic dependence for a system behaviour of a soiling        process of a surface of a motor vehicle, preferably derived by a        method for indirectly deriving a systematic dependence according        to one of the claims 1 to 14, for a resource efficient cleaning,        preferably resource-saving cleaning, of at least one surface of        a motor vehicle,        for optimizing a resource requirement for a cleaning process of        a surface of a motor vehicle, in particular by applying a method        for optimizing a resource requirement for a cleaning process of        a surface of a motor vehicle, preferably by applying a method        according to the third aspect of the invention.

Here the use of a dependency table, preferably a dependency table, whichwas created with the first steps of the procedure according to the ninthaspect of the invention and which describes the system behaviour of asoiling process of a surface of a motor vehicle, is proposed for theoptimization of a resource requirement of a cleaning process forcleaning the surface, in particular by applying a method according tothe third aspect of the invention.

Furthermore, the use of a systematic dependence describing the systembehaviour of the soiling process of the surface of the motor vehicle,preferably a systematic dependence according to the ninth aspect of theinvention, for the optimisation of the resource requirements of acleaning process for cleaning the surface is proposed here, inparticular by applying a method according to the third aspect of theinvention.

With regard to the dependency table and/or the systematic distance, whathas already been carried out under the tenth to eleventh aspect of thedependency table and/or the systematic distance applies with thenecessary adjustments.

Whereby the dependency table exhibits at least one input quantity of thesoiling process, in particular at least one input quantity according tothe ninth aspect of the invention. In particular, it is conceivable,among other things, that the dependency table may exhibit at least thedistance travelled by the motor vehicle between the first availabilityand the second availability and/or the operating time by covering thedistance travelled by the motor vehicle between the first availabilityand the second availability and/or a driving speed of the motor vehicle,preferably a course of the driving speed along the route between thefirst availability and the second availability, and/or a processquantity, preferably a humidity, particularly preferably a course of thehumidity along the route between the first availability and the secondavailability, and/or a temperature in the vicinity of the motor vehicle,particularly preferably a course of the temperature along the routebetween the first availability and the second availability, and/or arainfall, particularly preferably a course of the rainfall along theroute between the first availability and the second availability, and/ora snowfall quantity, particularly preferably a course of the snowfallquantity along the route between the first availability and the secondavailability, and/or a vehicle type and/or a coordinate of the motorvehicle, preferably the coordinate of the motor vehicle along the routebetween the first availability and the second availability, and/or thefirst availability of the sensor, and the evaluated change ofavailability. It should preferably be considered that the dependencytable shows the input quantity and the evaluated change of availabilityin an ordered way to each other.

When using the systematic dependence proposed here for use to determinean expected availability of the sensor, a systematic dependence whichexhibits at least one input quantity according to the systematicdependence derived with the ninth aspect of the invention could inparticular be considered.

It is understood that the advantages of a dependency table as describedabove and/or a systematic dependence as described above, in particularthe advantages of a dependency table created with the first steps of themethod after the ninth aspect of the invention and/or a systematicdependence according to the ninth aspect of the invention, as describedabove, directly extend to the use of a dependency table, preferably theuse of a dependency table created with the first steps of the methodafter the ninth aspect of the invention, and/or the use of a systematicdependence, preferably a systematic dependence according to the ninthaspect of the invention, for optimizing a resource requirement for acleaning process of a surface of a motor vehicle.

It should be pointed out that the above values for the number of datasets should not be understood as sharp limits, but rather should be ableto be exceeded or fallen below on an engineering scale without leavingthe described aspect of the invention. In simple terms, the values areintended to provide an indication of the size of the number of data setsproposed here.

It goes without saying that the advantages of systematic dependence, inparticular systematic dependence according to the ninth aspect of theinvention, also apply to the use of systematic dependence, in particularthe use of systematic dependence proposed here according to the twelfthaspect of the invention.

It should be noted that the subject-matter of the twelfth aspect can beadvantageously combined with the subject-matter of the preceding aspectsof the invention, either individually or cumulatively in anycombination.

According to a thirteenth aspect of the invention, the task is solved bya use of

-   -   a dependency table exhibiting at least two data sets, preferably        exhibiting at least 50 data sets, particularly preferably        exhibiting at least 200 data sets,    -   wherein each data set exhibits at least one input quantity of        the soiling process, in particular the distance travelled by the        motor vehicle between the first availability and the second        availability and/or the operating time by covering the distance        travelled by the motor vehicle between the first availability        and the second availability, and/or a driving speed of the motor        vehicle, preferably a course of the driving speed along the        route between the first availability and the second        availability, and/or a process quantity, preferably a humidity,        particularly preferably a course of the humidity along the route        between the first availability and the second availability,        and/or a temperature in the vicinity of the motor vehicle,        particularly preferably a course of the temperature along the        route between the first availability and the second        availability, and/or a rainfall, particularly preferably a        course of the rainfall along the route between the first        availability and the second availability, and/or a snowfall        quantity, particularly preferably a course of the snowfall        quantity along the route between the first availability and the        second availability, and/or a vehicle type and/or a coordinate        of the motor vehicle, preferably the coordinate of the motor        vehicle along the route between the first availability and the        second availability, and/or the first availability of the        sensor, and the evaluated change of availability, stored in an        ordered manner with reference to one another,    -   and/or    -   a systematic dependence for a system behaviour of a soiling        process of a surface of a motor vehicle, preferably derived by a        method for indirectly deriving a systematic dependence according        to one of the claims 1 to 14, for a resource efficient cleaning,        preferably resource-saving cleaning, of at least one surface of        a motor vehicle,        to determine a cleaning strategy for cleaning a surface to be        cleaned of a motor vehicle,        in particular by applying a method for determining a cleaning        strategy for cleaning a surface to be cleaned of a motor        vehicle, preferably by applying a method to determine a cleaning        strategy according to the fourth aspect of the invention.

Here the use of a dependency table, preferably a dependency table, whichwas created with the first steps of the procedure according to the ninthaspect of the invention and which describes the system behaviour of asoiling process of a surface of a motor vehicle, is proposed todetermine a cleaning strategy for cleaning the surface of the motorvehicle, in particular by applying a method according to the fourthaspect of the invention.

Furthermore, the use of a systematic dependence describing the systembehaviour of the soiling process of the surface of the motor vehicle,preferably a systematic dependence according to the ninth aspect of theinvention, is proposed here for the determination of the cleaningstrategy for cleaning the surface, in particular by applying a methodaccording to the fourth aspect of the invention.

With regard to the dependency table and/or the systematic distance, whathas already been carried out under the tenth to twelfth aspect of thedependency table and/or the systematic distance applies with thenecessary adjustments.

Whereby the dependency table exhibits at least one input quantity of thesoiling process, in particular at least one input quantity according tothe ninth aspect of the invention. In particular, it is conceivable,among other things, that the dependency table may exhibit at least thedistance travelled by the motor vehicle between the first availabilityand the second availability and/or the operating time by covering thedistance travelled by the motor vehicle between the first availabilityand the second availability and/or a driving speed of the motor vehicle,preferably a course of the driving speed along the route between thefirst availability and the second availability, and/or a processquantity, preferably a humidity, particularly preferably a course of thehumidity along the route between the first availability and the secondavailability, and/or a temperature in the vicinity of the motor vehicle,particularly preferably a course of the temperature along the routebetween the first availability and the second availability, and/or arainfall, particularly preferably a course of the rainfall along theroute between the first availability and the second availability, and/ora snowfall quantity, particularly preferably a course of the snowfallquantity along the route between the first availability and the secondavailability, and/or a vehicle type and/or a coordinate of the motorvehicle, preferably the coordinate of the motor vehicle along the routebetween the first availability and the second availability, and/or thefirst availability of the sensor, and the evaluated change ofavailability. It should preferably be considered that the dependencytable shows the input quantity and the evaluated change of availabilityin an ordered way to each other.

When using the systematic dependence proposed here for use to determinean expected availability of the sensor, a systematic dependence whichexhibits at least one input quantity according to the systematicdependence derived with the ninth aspect of the invention could inparticular be considered.

It is understood that the advantages of a dependency table as describedabove and/or a systematic dependence as described above, in particularthe advantages of a dependency table created with the first steps of themethod after the ninth aspect of the invention and/or a systematicdependence according to the ninth aspect of the invention, as describedabove, directly extend to the use of a dependency table, preferably theuse of a dependency table created with the first steps of the methodafter the ninth aspect of the invention, and/or the use of a systematicdependence, preferably a systematic dependence according to the ninthaspect of the invention, to determine a cleaning strategy for cleaning asurface to be cleaned of a motor vehicle.

It should be pointed out that the above values for the number of datasets should not be understood as sharp limits, but rather should be ableto be exceeded or fallen below on an engineering scale without leavingthe described aspect of the invention. In simple terms, the values areintended to provide an indication of the size of the number of data setsproposed here.

It goes without saying that the advantages of systematic dependence, inparticular systematic dependence according to the ninth aspect of theinvention, also apply to the use of systematic dependence, in particularthe use of systematic dependence proposed here according to thethirteenth aspect of the invention.

It should be noted that the subject-matter of the thirteenth aspect canbe advantageously combined with the subject-matter of the precedingaspects of the invention, either individually or cumulatively in anycombination.

According to a fourteenth aspect of the invention, the task is solved bya use of

-   -   a dependency table exhibiting at least two data sets, preferably        exhibiting at least 50 data sets, particularly preferably        exhibiting at least 200 data sets,    -   wherein each data set exhibits at least one input quantity of        the soiling process, in particular the distance travelled by the        motor vehicle between the first availability and the second        availability and/or the operating time by covering the distance        travelled by the motor vehicle between the first availability        and the second availability, and/or a driving speed of the motor        vehicle, preferably a course of the driving speed along the        route between the first availability and the second        availability, and/or a process quantity, preferably a humidity,        particularly preferably a course of the humidity along the route        between the first availability and the second availability,        and/or a temperature in the vicinity of the motor vehicle,        particularly preferably a course of the temperature along the        route between the first availability and the second        availability, and/or a rainfall, particularly preferably a        course of the rainfall along the route between the first        availability and the second availability, and/or a snowfall        quantity, particularly preferably a course of the snowfall        quantity along the route between the first availability and the        second availability, and/or a vehicle type and/or a coordinate        of the motor vehicle, preferably the coordinate of the motor        vehicle along the route between the first availability and the        second availability, and/or the first availability of the        sensor, and the evaluated change of availability, stored in an        ordered manner with reference to one another,    -   and/or    -   a systematic dependence for a system behaviour of a soiling        process of a surface of a motor vehicle, preferably derived by a        method for indirectly deriving a systematic dependence according        to one of the claims 1 to 14, for a resource efficient cleaning,        preferably resource-saving cleaning, of at least one surface of        a motor vehicle,        to determine a necessary expected gain in availability, whereby        the sum of the actual availability and the necessary expected        gain in availability is sufficient to achieve a distance or an        operating time yet to be covered by the motor vehicle in such a        way that a threshold of availability is not exceeded, by    -   parallel displacement of the systematic dependence in the        direction of the dimension of the distance or the operating time        until the intersection between the threshold of availability and        the displaced systematic dependence reaches the distance or the        operating time yet to be covered by the motor vehicle and        determination of the necessary expected gain in availability        starting from the actual availability,    -   or    -   parallel displacement of the data sets from the dependency table        in the direction of the dimension of the distance or the        operating time until the data set from the dependency table that        best matches the intersection between the threshold of        availability and the distance or the operating time yet to be        covered by the motor vehicle has exceeded the intersection point        in direction of the distance or the operating time and        determination of the necessary expected gain in availability        between the data set from the dependency table that best matches        the actual point in time and the actual availability starting        from the actual availability    -   or    -   parallel displacement of the data sets from the dependency table        in the direction of the dimension of the distance or the        operating time until the linear interpolation between the        adjacent data sets of the dependency table that best match the        intersection between the threshold of availability and the        distance or the operating time yet to be covered by the motor        vehicle has exceeded the intersection point in direction of the        distance or the operating time and determination of the        necessary expected gain in availability the linear interpolation        between the adjacent data sets of the dependency table that best        match the actual point in time and the actual availability        starting from the actual availability.

In accordance with the fourteenth aspect of the invention, a method fordetermining a necessary expected gain in availability is proposed here,whereby the sum of the actual availability and the necessary expectedgain in availability is sufficient to achieve a distance or an operatingtime yet to be covered by the motor vehicle.

In other words, the objective of the method proposed here is todetermine the amount by which the availability of a sensor is expectedto be improved, in particular by means of an appropriate cleaningprocess to clean the surface in active contact with the sensor so thatthe pre-planned route or operating time of the vehicle can still becovered without reaching a threshold of availability associated with thesensor.

If a sensor falls below its associated threshold of availability, it isapparent that the sensor can no longer provide data or that the dataprovided by the sensor is no longer of sufficient quality for furtherprocessing in certain driver assistance systems, so that the relevantdriver assistance systems can no longer be used until the availabilityassociated with the sensor is again above the corresponding threshold ofavailability.

In this context, a threshold of availability can be understood as atarget value for expected availability, in particular to indirectlydetermine an event which should not occur until the end of thepre-planned operating time or route, i.e. a fall below a threshold ofavailability.

In accordance with the fourteenth aspect of the invention, it isconcretely proposed here to use a dependency table, in particular adependency table which has arisen with the first steps of the procedureaccording to the ninth aspect of the invention, and/or a systematicdependency, in particular a systematic dependency derived according tothe ninth aspect of the invention, for the determination of a necessarygain in availability which is sufficient to ensure as expected that anavailability of a sensor until the end of the pre-planned route and/oruntil the end of the pre-planned operating time does not assume a valuewhich is smaller than the threshold of availability associated with thesensor. In particular, it could be considered that a necessary gain inavailability based on the actual availability is sufficient so that anexpected availability at the end of the pre-planned route and/or thepre-planned operating time is greater than or equal to the threshold ofavailability.

With regard to the dependency table and/or the systematic distance, whathas already been carried out under the tenth to thirteenth aspect of thedependency table and/or the systematic distance applies with thenecessary adjustments.

Whereby the dependency table exhibits at least one input quantity of thesoiling process, in particular at least one input quantity according tothe ninth aspect of the invention. In particular, it is conceivable,among other things, that the dependency table may exhibit at least thedistance travelled by the motor vehicle between the first availabilityand the second availability and/or the operating time by covering thedistance travelled by the motor vehicle between the first availabilityand the second availability and/or a driving speed of the motor vehicle,preferably a course of the driving speed along the route between thefirst availability and the second availability, and/or a processquantity, preferably a humidity, particularly preferably a course of thehumidity along the route between the first availability and the secondavailability, and/or a temperature in the vicinity of the motor vehicle,particularly preferably a course of the temperature along the routebetween the first availability and the second availability, and/or arainfall, particularly preferably a course of the rainfall along theroute between the first availability and the second availability, and/ora snowfall quantity, particularly preferably a course of the snowfallquantity along the route between the first availability and the secondavailability, and/or a vehicle type and/or a coordinate of the motorvehicle, preferably the coordinate of the motor vehicle along the routebetween the first availability and the second availability, and/or thefirst availability of the sensor, and the evaluated change ofavailability. It should preferably be considered that the dependencytable shows the input quantity and the evaluated change of availabilityin an ordered way to each other.

When using the systematic dependence proposed here for use to determinean expected availability of the sensor, a systematic dependence whichexhibits at least one input quantity according to the systematicdependence derived with the ninth aspect of the invention could inparticular be considered.

The method proposed here provides a necessary expected gain inavailability for each individually considered sensor, which issufficient according to the experience values made to ensure that anavailability of the respective sensor until the end of the pre-plannedroute and/or until the end of the pre-planned operating time does notassume a value which is smaller than the threshold of availabilityassociated with the sensor, and must be executed again in order toobtain a necessary expected gain in availability for another sensor.

Under real conditions, a different necessary expected gain inavailability often results for each sensor considered, which can partlybe explained by the different soiling status and the different systembehaviour of the respective soiling process.

The procedure proposed here can be described in particular by thefollowing variants of characterizing procedural steps:

According to a first variant, it is proposed here to determine theexpected gain in availability, which is necessarily still required, onthe basis of the already known pre-planned distance to be covered by themotor vehicle and/or on the basis of the already known pre-plannedoperating time on the basis of the systematic dependence, whereby thesystematic dependence describes the system behaviour of the soilingprocess.

For this purpose the input quantity, which also includes the pre-planneddistance to be covered and/or the pre-planned operating time to becovered, is used in the systematic dependence. The function value ofsystematic dependence is a change of availability.

The change in availability thus obtained is summed up with the thresholdof availability. The sum of the threshold of availability and the changeof availability is the necessary expected availability.

If the necessary expected availability is greater than the actualavailability, the necessary expected gain in availability is zero.

If the necessary expected availability is less than the actualavailability, the necessary expected gain in availability is thedifference between the necessary expected availability and the actualavailability.

It should be expressly pointed out that the variant of the proceduredescribed above corresponds to a parallel displacement of the systematicdependence in the direction of the dimension of the distance or theoperating time until the intersection between the threshold ofavailability and the displaced systematic dependence reaches thedistance or the operating time yet to be covered by the motor vehicleand determination of the necessary expected gain in availabilitystarting from the actual availability if the necessary expected gain inavailability is determined graphically.

According to a second variant of the procedure, it is also proposed toplan the expected gain in availability, which is necessarily stillrequired, on the basis of experience values in the form of data sets ofa dependency table, based on the already known pre-planned distance tobe covered by the motor vehicle and/or based on the already knownpre-planned operating time, whereby the data sets from the dependencytable describe the system behaviour of the soiling process.

It is suggested to select a data set with empirical values from thedependency table. For this, the data set is selected whose inputquantity best matches the case considered here, in particular whoseinput quantity best matches the pre-planned distance and/or operatingtime to be covered and the other variables recorded in the inputquantity. The corresponding change of availability can then be takenfrom this data set.

In particular, it is suggested to select the most suitable data set overthe smallest Euclidean distance of all data sets of the dependencytable.

The resulting change in availability is summed with the threshold ofavailability. The sum of the threshold of availability and the change ofavailability is the necessary expected availability.

If the necessary expected availability is greater than the actualavailability, the necessary expected gain in availability is zero.

If the necessary expected availability is less than the actualavailability, the necessary expected gain in availability is thedifference between the necessary expected availability and the actualavailability.

It should be expressly pointed out that the variant of the proceduredescribed above corresponds to a parallel displacement of the data setsfrom the dependency table in the direction of the dimension of thedistance or the operating time until the data set from the dependencytable that best matches the intersection between the threshold ofavailability and the distance or the operating time yet to be covered bythe motor vehicle has exceeded the intersection point in direction ofthe distance or the operating time and determination of the necessaryexpected gain in availability between the data set from the dependencytable that best matches the actual point in time and the actualavailability starting from the actual availability if the necessaryexpected gain in availability is determined graphically.

According to a third variant, it is proposed to modify the variantaccording to the second variant to select the two most suitable datasets from the dependency table instead of one data set, whereby thechange of availability is determined by linear interpolation between thetwo selected data sets. Further components of the procedure can be takenfrom the second variant.

It should be expressly pointed out that the variant of the proceduredescribed above corresponds to a parallel displacement of the data setsfrom the dependency table in the direction of the dimension of thedistance or the operating time until the linear interpolation betweenthe adjacent data sets of the dependency table that best match theintersection between the threshold of availability and the distance orthe operating time yet to be covered by the motor vehicle has exceededthe intersection point in direction of the distance or the operatingtime and determination of the necessary expected gain in availabilitythe linear interpolation between the adjacent data sets of thedependency table that best match the actual point in time and the actualavailability starting from the actual availability if the necessaryexpected gain in availability is determined graphically.

It should be expressly pointed out that the point of valuation for thedetermination of the necessary expected gain in availability accordingto the above variants can also lie in the future, which can be relevantin particular for the advance planning of a cleaning resource-optimalcleaning process of the surface in an effective connection with thesensor, in particular for the planning of a cleaning resource-optimalcleaning process according to the third aspect of the invention. If thevaluation date is in the future, the above variants of the method mustonly be modified in such a way that the actual availability correspondsto an expected availability at the planning time. The correspondingexpected availability at the planning time can be determined inparticular with a method according to the tenth aspect of the invention.

It should be expressly pointed out that the actual availability in allthree variants is supplied by the sensor or can otherwise be derivedfrom the data provided by the corresponding sensor.

This makes it advantageously possible to determine whether a surfacethat is in an active connection with a sensor still needs to be cleanedin order to maintain the currently selected driver assistance systems inorder to cover the planned distance and/or the planned operating time,or whether the planned goal can still be achieved even without theassociated cleaning process, without the associated threshold ofavailability being undercut.

Furthermore, in the case where a cleaning process is necessary, thenecessary gain of availability can be determined directly, which isrequired to ensure that the availability of the sensor does not fallbelow the corresponding threshold of availability according to thepreplanned objective.

This enables a more precise planning of a cleaning process for a surfaceas well as an optimal planning of a cleaning process, especially after athird aspect of the invention.

Furthermore, with this fourteenth aspect of the invention a planning ofa cleaning resource-optimal cleaning strategy is advantageously madepossible, in particular the determination of a cleaning strategy afterthe fourth aspect of the invention.

It can also be achieved so advantageously that by means of the necessarycleaning process that can be determined, the resource requirement ofcleaning resources can be determined that is still required when thepre-planned distance to travel and/or the pre-planned operating time totravel is covered. If this resource requirement can no longer be coveredby the stock of cleaning resources carried in the motor vehicle, acorresponding maintenance stop can be planned to replenish cleaningresources, especially advantageously by means of a navigation system setup accordingly.

In particular, the aspect presented here can be used to advantage toensure that the cleaning of a surface that is operatively connected to asensor can always be carried out in such a way that the motor vehicleachieves the goal of active motor vehicle use with the cleaning effortthat is just necessary without losing the functionality of driverassistance systems.

As a rule, a phase with active vehicle operation is followed by a phaseof passive vehicle operation in which the vehicle is parked and waitingfor its next active vehicle operation.

In this phase of passive vehicle operation, the availability of a sensorusually also changes, especially due to weather-related influences onthe vehicle. This change in availability can lead to both a decrease andan increase in availability, especially if the parked vehicle is exposedto rain and/or snow.

This change in the availability of a motor vehicle during passive motorvehicle operation is initially not relevant for passive motor vehicleoperation, since the use of sensors is generally only conditional onactive motor vehicle operation. In this respect, the question of theavailability of a sensor only arises again when active vehicle operationis resumed.

It turned out unexpectedly that a cleaning strategy in which theavailability of each sensor is just above the respective thresholds ofavailability can save the most cleaning resources overall. This can beadvantageously achieved by the aspect presented here, particularly incombination with the third and fourth aspects of the invention.

The operating time that can be determined here, among other things, canbe of particular interest to professional drivers. In particular, theoperation of a taxi should be considered, which is in active use until acertain time of day and during this time should make as many journeys aspossible and as few maintenance stops as possible. In this respect, astatement with a possible remaining operating time for this type ofmotor vehicle operation may be more relevant than a statement linked toa distance that can still be covered.

It should be pointed out that the above values for the number of datasets should not be understood as sharp limits, but rather should be ableto be exceeded or fallen below on an engineering scale without leavingthe described aspect of the invention. In simple terms, the values areintended to provide an indication of the size of the number of data setsproposed here.

It goes without saying that the advantages of systematic dependence, inparticular systematic dependence according to the ninth aspect of theinvention, also apply to the use of systematic dependence, in particularthe use of systematic dependence proposed here according to thefourteenth aspect of the invention.

It should be noted that the subject-matter of the fourteenth aspect canbe advantageously combined with the subject-matter of the precedingaspects of the invention, either individually or cumulatively in anycombination.

According to a fifteenth aspect of the invention, the task is solved bya use of a systematic dependence derived by a method for indirectlyderiving a systematic dependence for a system behavior of a cleaningsystem of a motor vehicle according to the second aspect of theinvention for a resource efficient cleaning, preferably resource-savingcleaning, of at least one surface of a motor vehicle, and/or a use of acontrol quantity setpoint derived by a method for optimizing a resourcerequirement for a cleaning process of a surface of a motor vehicleaccording to the third aspect of the invention for a resource efficientcleaning, preferably resource-saving cleaning, of at least one surfaceof a motor vehicle, and/or a use of a cleaning strategy derived by amethod according to the fourth aspect of the invention for a resourceefficient cleaning, preferably resource-saving cleaning, of at least onesurface of a motor vehicle.

It is understood that the advantages of a systematic dependence derivedby a method for indirectly deriving a systematic dependence for a systembehavior of a cleaning system of a motor vehicle according to the secondaspect of the invention for a resource efficient cleaning, preferablyresource-saving cleaning, of at least one surface of a motor vehicle,and/or the advantages of a control quantity setpoint derived by a methodfor optimizing a resource requirement for a cleaning process of asurface of a motor vehicle according to the third aspect of theinvention for a resource efficient cleaning, preferably resource-savingcleaning, of at least one surface of a motor vehicle, and/or theadvantages of a cleaning strategy derived by a method according to thefourth aspect of the invention for a resource efficient cleaning,preferably resource-saving cleaning, of at least one surface of a motorvehicle, as described above, directly extend to a use of a systematicdependence derived by a method for indirectly deriving a systematicdependence for a system behavior of a cleaning system of a motor vehicleaccording to the second aspect of the invention for a resource efficientcleaning, preferably resource-saving cleaning, of at least one surfaceof a motor vehicle, and/or a use of a control quantity setpoint derivedby a method for optimizing a resource requirement for a cleaning processof a surface of a motor vehicle according to the third aspect of theinvention for a resource efficient cleaning, preferably resource-savingcleaning, of at least one surface of a motor vehicle, and/or a use of acleaning strategy derived by a method according to the fourth aspect ofthe invention for a resource efficient cleaning, preferablyresource-saving cleaning, of at least one surface of a motor vehicle.

It should be noted that the subject-matter of the fifteenth aspect ofthe invention can be advantageously combined with the subject-matter ofthe preceding aspects of the invention, either individually orcumulatively in any combination.

According to a sixteenth aspect of the invention, the task is solved bya cleaning system exhibiting an electronic control unit, a cleaningfluid distribution system, wherein the cleaning fluid distributionsystem comprises at least one fluid reservoir, at least one nozzle, andat least one cleaning fluid line, wherein the cleaning system is adaptedto execute a cleaning method for a resource efficient cleaning,preferably resource-saving cleaning, of at least one surface of a motorvehicle according to the first aspect of the invention, and/or whereinthe cleaning system is adapted to execute a method for indirectlyderiving a systematic dependence for a system behaviour of a cleaningsystem of a motor vehicle, particularly for a system behaviour of acleaning process of a surface of the motor vehicle, according to thesecond aspect of the invention, and/or wherein the cleaning system isadapted to execute a method for optimizing a resource requirement for acleaning process of a surface of a motor vehicle, wherein a sensor isoperatively connected to the surface according to the third aspect ofthe invention, and/or wherein the cleaning system is adapted to executea method for determining a cleaning strategy for cleaning a surface tobe cleaned of a motor vehicle according to the fourth aspect of theinvention, and/or wherein the cleaning system is adapted to execute amethod for indirectly deriving a systematic dependence for a systembehaviour of a system component of a cleaning system of a motor vehicleaccording to the fifth aspect of the invention, and/or adapted toexecute a method for diagnosing a deviation between an actual systembehaviour of a system component of a cleaning system of a motor vehicleaccording to the sixth aspect of the invention, and/or adapted toexecute a method for selecting a resolution strategy from a list ofresolution strategies contained in a database according to the seventhaspect of the invention, and/or adapted to use a selected resolutionstrategy according to the eighth aspect of the invention, and/or whereinthe cleaning system is adapted to execute a method for indirectlyderiving a systematic dependence for a system behaviour of a soilingprocess of a surface of a motor vehicle according to the ninth aspect ofthe invention, and/or whereby the motor vehicle is adapted to use adependency table and/or a systematic dependence according to the tenthand/or the eleventh and/or the twelfth and/or the thirteens and/or thefourteenth aspect of the invention.

It is understood that the advantages of a cleaning method for a resourceefficient cleaning, preferably resource-saving cleaning, of at least onesurface of a motor vehicle according to the first aspect of theinvention, and/or the advantages of a method for indirectly deriving asystematic dependence for a system behaviour of a cleaning system of amotor vehicle, particularly for a system behaviour of a cleaning processof a surface of the motor vehicle, according to the second aspect of theinvention, and/or the advantages of a method for optimizing a resourcerequirement for a cleaning process of a surface of a motor vehicle,wherein a sensor is operatively connected to the surface according tothe third aspect of the invention, and/or the advantages of a method fordetermining a cleaning strategy for cleaning a surface to be cleaned ofa motor vehicle according to the fourth aspect of the invention, and/orthe advantages of a method for indirectly deriving a systematicdependence for a system behaviour of a system component of a cleaningsystem of a motor vehicle according to the fifth aspect of theinvention, and/or the advantages of a method for diagnosing a deviationbetween an actual system behaviour of a system component of a cleaningsystem of a motor vehicle according to the sixth aspect of theinvention, and/or the advantages of a method for selecting a resolutionstrategy from a list of resolution strategies contained in a databaseaccording to the seventh aspect of the invention, and/or the advantagesof a selected resolution strategy according to the eighth aspect of theinvention, and/or the advantages of a method for indirectly deriving asystematic dependence for a system behaviour of a soiling process of asurface of a motor vehicle according to the ninth aspect of theinvention, and/or the advantages of a use of a dependency table and/or asystematic dependence according to the tenth and/or the eleventh and/orthe twelfth and/or the thirteens and/or the fourteenth aspect of theinvention, as described above, directly extend to a cleaning systemexhibiting an electronic control unit, a cleaning fluid distributionsystem, wherein the cleaning fluid distribution system comprises atleast one fluid reservoir, at least one nozzle, and at least onecleaning fluid line, wherein the cleaning system is adapted to execute acleaning method for a resource efficient cleaning, preferablyresource-saving cleaning, of at least one surface of a motor vehicleaccording to the first aspect of the invention, and/or wherein thecleaning system is adapted to execute a method for indirectly deriving asystematic dependence for a system behaviour of a cleaning system of amotor vehicle, particularly for a system behaviour of a cleaning processof a surface of the motor vehicle, according to the second aspect of theinvention, and/or wherein the cleaning system is adapted to execute amethod for optimizing a resource requirement for a cleaning process of asurface of a motor vehicle, wherein a sensor is operatively connected tothe surface according to the third aspect of the invention, and/orwherein the cleaning system is adapted to execute a method fordetermining a cleaning strategy for cleaning a surface to be cleaned ofa motor vehicle according to the fourth aspect of the invention, and/orwherein the cleaning system is adapted to execute a method forindirectly deriving a systematic dependence for a system behaviour of asystem component of a cleaning system of a motor vehicle according tothe fifth aspect of the invention, and/or adapted to execute a methodfor diagnosing a deviation between an actual system behaviour of asystem component of a cleaning system of a motor vehicle according tothe sixth aspect of the invention, and/or adapted to execute a methodfor selecting a resolution strategy from a list of resolution strategiescontained in a database according to the seventh aspect of theinvention, and/or adapted to use a selected resolution strategyaccording to the eighth aspect of the invention, and/or wherein thecleaning system is adapted to execute a method for indirectly deriving asystematic dependence for a system behaviour of a soiling process of asurface of a motor vehicle according to the ninth aspect of theinvention, and/or whereby the motor vehicle is adapted to use adependency table and/or a systematic dependence according to the tenthand/or the eleventh and/or the twelfth and/or the thirteens and/or thefourteenth aspect of the invention.

It should be noted that the subject-matter of the sixteenth aspect ofthe invention can be advantageously combined with the subject-matter ofthe preceding aspects of the invention, either individually orcumulatively in any combination.

According to a seventeenth aspect of the invention, the task is solvedby a motor vehicle, whereby the motor vehicle exhibits a cleaning systemaccording to the sixteenth aspect of the invention, and/or whereby themotor vehicle is adapted to execute a cleaning method for a resourceefficient cleaning, preferably resource-saving cleaning, of at least onesurface of the motor vehicle according to the first aspect of theinvention, and/or whereby the motor vehicle is adapted to execute amethod for indirectly deriving s systematic dependence for a systembehavior of a cleaning system of a motor vehicle according to the secondaspect of the invention, and/or adapted to use a systematic dependencederived according to the second aspect of the invention for a resourceefficient cleaning, preferably resource-saving cleaning, of at least onesurface of the motor vehicle, and/or whereby the motor vehicle isadapted to execute a method for optimizing a resource requirement for acleaning process of a surface of a motor vehicle according to the thirdaspect of the invention, and/or adapted to use a control quantitysetpoint derived by a method for optimizing a resource requirement for acleaning process of a surface of a motor vehicle according to the thirdaspect of the invention for a resource efficient cleaning, preferablyresource-saving cleaning, of at least one surface of the motor vehicle,and/or whereby the motor vehicle is adapted to execute a method fordetermining a cleaning strategy for cleaning a surface to be cleaned ofa motor vehicle according to the fourth aspect of the invention, and/oradapted to use a cleaning strategy derived by a method for determining acleaning strategy for cleaning a surface to be cleaned of a motorvehicle according to the fourth aspect of the invention for a resourceefficient cleaning, preferably resource-saving cleaning, of at least onesurface of the motor vehicle, and/or whereby the motor vehicle isadapted to execute a method for indirectly deriving a systematicdependence for a system behaviour of a system component of a cleaningsystem of a motor vehicle according to the fifth aspect of theinvention, and/or adapted to execute a method for diagnosing a deviationbetween an actual system behaviour of a system component of a cleaningsystem of a motor vehicle according to the sixth aspect of theinvention, and/or adapted to execute a method for selecting a resolutionstrategy from a list of resolution strategies contained in a databaseaccording to the seventh aspect of the invention, and/or adapted to usea selected resolution strategy according to the eighth aspect of theinvention, and/or whereby the motor vehicle is adapted to execute amethod for indirectly deriving a systematic dependence for a systembehaviour of a soiling process of a surface of a motor vehicle accordingto the ninth aspect of the invention, and/or whereby the motor vehicleis adapted to use a dependency table and/or a systematic dependenceaccording to the tenth and/or the eleventh and/or the twelfth and/or thethirteens and/or the fourteenth aspect of the invention.

It is understood that the advantages of a cleaning system according tothe sixteenth aspect of the invention and/or the advantages of acleaning method for a resource efficient cleaning, preferablyresource-saving cleaning, of at least one surface of a motor vehicleaccording to the first aspect of the invention, and/or the advantages ofa systematic dependence according to the second aspect of the inventionfor a resource efficient cleaning, preferably resource-saving cleaning,of at least one surface of the motor vehicle, and/or the advantagesusing a systematic dependence derived according to the second aspect ofthe invention for a resource efficient cleaning, preferablyresource-saving cleaning, of at least one surface of the motor vehicle,and/or the advantages of a method for optimizing a resource requirementfor a cleaning process of a surface of a motor vehicle according to thethird aspect of the invention, and/or the advantages of a controlquantity setpoint derived by a method for optimizing a resourcerequirement for a cleaning process of a surface of a motor vehicleaccording to the third aspect of the invention for a resource efficientcleaning, preferably resource-saving cleaning, of at least one surfaceof the motor vehicle, and/or the advantages of a method for determininga cleaning strategy for cleaning a surface to be cleaned of a motorvehicle according to the fourth aspect of the invention, and/or theadvantages of a use of a cleaning strategy derived by a method fordetermining a cleaning strategy for cleaning a surface to be cleaned ofa motor vehicle according to the fourth aspect of the invention for aresource efficient cleaning, preferably resource-saving cleaning, of atleast one surface of the motor vehicle, and/or the advantages of amethod for indirectly deriving a systematic dependence for a systembehaviour of a system component of a cleaning system of a motor vehicleaccording to the fifth aspect of the invention, and/or the advantages ofa method for diagnosing a deviation between an actual system behaviourof a system component of a cleaning system of a motor vehicle accordingto the sixth aspect of the invention, and/or the advantages of a methodfor selecting a resolution strategy from a list of resolution strategiescontained in a database according to the seventh aspect of theinvention, and/or the advantages of a use of a selected resolutionstrategy according to the eighth aspect of the invention, and/or theadvantages of a method for indirectly deriving a systematic dependencefor a system behaviour of a soiling process of a surface of a motorvehicle according to the ninth aspect of the invention, and/or theadvantages of a use of a dependency table and/or a systematic dependenceaccording to the tenth and/or the eleventh and/or the twelfth and/or thethirteens and/or the fourteenth aspect of the invention, as describedabove, directly extend to a motor vehicle, whereby the motor vehicleexhibits a cleaning system according to the sixteenth aspect of theinvention, and/or whereby the motor vehicle is adapted to execute acleaning method for a resource efficient cleaning, preferablyresource-saving cleaning, of at least one surface of the motor vehicleaccording to the first aspect of the invention, and/or whereby the motorvehicle is adapted to execute a method for indirectly deriving ssystematic dependence for a system behavior of a cleaning system of amotor vehicle according to the second aspect of the invention, and/oradapted to use a systematic dependence derived according to the secondaspect of the invention for a resource efficient cleaning, preferablyresource-saving cleaning, of at least one surface of the motor vehicle,and/or whereby the motor vehicle is adapted to execute a method foroptimizing a resource requirement for a cleaning process of a surface ofa motor vehicle according to the third aspect of the invention, and/oradapted to use a control quantity setpoint derived by a method foroptimizing a resource requirement for a cleaning process of a surface ofa motor vehicle according to the third aspect of the invention for aresource efficient cleaning, preferably resource-saving cleaning, of atleast one surface of the motor vehicle, and/or whereby the motor vehicleis adapted to execute a method for determining a cleaning strategy forcleaning a surface to be cleaned of a motor vehicle according to thefourth aspect of the invention, and/or adapted to use a cleaningstrategy derived by a method for determining a cleaning strategy forcleaning a surface to be cleaned of a motor vehicle according to thefourth aspect of the invention for a resource efficient cleaning,preferably resource-saving cleaning, of at least one surface of themotor vehicle, and/or whereby the motor vehicle is adapted to execute amethod for indirectly deriving a systematic dependence for a systembehaviour of a system component of a cleaning system of a motor vehicleaccording to the fifth aspect of the invention, and/or adapted toexecute a method for diagnosing a deviation between an actual systembehaviour of a system component of a cleaning system of a motor vehicleaccording to the sixth aspect of the invention, and/or adapted toexecute a method for selecting a resolution strategy from a list ofresolution strategies contained in a database according to the seventhaspect of the invention, and/or adapted to use a selected resolutionstrategy according to the eighth aspect of the invention, and/or wherebythe motor vehicle is adapted to execute a method for indirectly derivinga systematic dependence for a system behaviour of a soiling process of asurface of a motor vehicle according to the ninth aspect of theinvention, and/or whereby the motor vehicle is adapted to use adependency table and/or a systematic dependence according to the tenthand/or the eleventh and/or the twelfth and/or the thirteens and/or thefourteenth aspect of the invention.

It should be noted that the subject-matter of the seventeenth aspect ofthe invention can be advantageously combined with the subject-matter ofthe preceding aspects of the invention, either individually orcumulatively in any combination.

Further advantages, details and features of the present invention areexplained in the description of the following embodiments, thereby:

FIG. 1 : shows a schematic view of a motor vehicle exhibiting a cleaningsystem;

FIG. 2 : shows a schematic view of a cleaning method exhibiting asequence of multiple cleaning processes for a plurality of surfaces tobe cleaned as a function of a course of time;

FIG. 3 : shows a schematic view of a subtraction procedure to determinea difference from the measured values of a measured quantity;

FIG. 4 : shows a schematic view of systematic dependencies betweenvalues of quantities;

FIG. 5 : shows a schematic view of a cleaning device;

FIG. 6 : shows a schematic view of a data processing system;

FIG. 7 : shows a schematic view of a system, preferably a cleaningsystem;

FIG. 8 : shows a schematic view of a motor vehicle with an air jetcleaning system;

FIG. 9 : shows a schematic view of a motor vehicle exhibiting a cleaningsystem with a plurality of cleaning fluid pumps and cleaning fluid multiway valves;

FIG. 10 : shows a schematic view of a flowchart of a method forindirectly deriving a systematic dependence for a system behaviour of acleaning system of a motor vehicle, particularly for a system behaviourof a cleaning process of a surface of the motor vehicle;

FIG. 11 : shows a schematic view of a flowchart of a method foroptimizing a resource requirement for a cleaning process of a surface ofa motor vehicle;

FIG. 12 : shows a schematic view of a flowchart of a method fordetermining a cleaning strategy for cleaning a surface to be cleaned ofa motor vehicle;

FIG. 13 : shows a schematic representation of an availability history;

FIG. 14 : shows a schematic representation of an availability history;

FIG. 15 : shows a procedure in schematic view to determine an expectedavailability at a distance or operating time of the motor vehicle yet tobe covered;

FIG. 16 : shows a procedure in schematic view to determine an expecteddistance or operating time of the motor vehicle yet to be covered whenreaching a threshold of availability;

FIG. 17 : shows a procedure in schematic view to determine an expectedgain in availability, whereby the sum of the current availability andthe expected gain in availability is sufficient to achieve a distance oroperating time to be covered by the motor vehicle in such a way that athreshold of availability is not exceeded;

FIG. 18 : shows a schematic of a flow chart for a diagnostic method fora cleaning system; and

FIG. 19 : shows a schematic view of a flow chart of a cleaning method.

In the following description same reference numerals describe sameelements and same features, respectively, so that a description of oneelement conducted with reference to one figure is also valid for theother figures, so that repetition of the respective feature is omitted.

The motor vehicle 14 in FIG. 1 is equipped with a cleaning system 16,which provides structural elements 18, 60, 62, 70, 72, 74, 76 a, 76 b,78 a, 78 b, 80, 82, 84, 86, 88, 90, 92, 94 required for a physicalcleaning process (not depicted) to clean a surface 20, 22, 24, 26, 28 ofa motor vehicle 14 to be cleaned.

These structural elements 18, 60, 62, 70, 72, 74, 76 a, 76 b, 78 a, 78b, 80, 82, 84, 86, 88, 90, 92, 94 of the cleaning system 16 arepreferably a cleaning fluid distribution system 60 and other electrical(not depicted) and/or electronic components, preferably an electroniccontrol unit 18.

The cleaning fluid distribution system 60 is preferably understood as asystem designed to provide a designated cleaning fluid 64 from acleaning fluid reservoir 62, which is designed to store the designatedcleaning fluid 64, preferably by means of a cleaning fluid line 80, 82,84, 86, 88, designed to guide the designated cleaning fluid 64, and anozzle 70, 72, 74, 76 a, 76 b, 78 a, 78 b on a surface 20, 22, 24, 26,28 of a motor vehicle 14 to be cleaned.

Preferably a cleaning fluid distribution system 60 is equipped with anelectric pump (not depicted), which is designed to pump the designatedcleaning fluid 64, and which is preferably integrated into the cleaningfluid reservoir 62.

The nozzle 70, 72, 74, 76 a, 76 b, 78 a, 78 b is a device through whichthe designated cleaning fluid 64 can leave the cleaning system 16 andwhich is designed to bring the designated cleaning fluid 64 into aninteraction, preferably an operative connection, with the surface 20,22, 24, 26, 28 to be cleaned.

Preferably the nozzle 70, 72, 74, 76 a, 76 b, 78 a, 78 b is a devicedesigned to control a direction (unmarked) or a characteristics (notdepicted) of the designated cleaning fluid 64 as it exits the cleaningfluid distribution system 60.

Preferably, the nozzle 70, 72, 74, 76 a, 76 b, 78 a, 78 b exhibitsactuating means (not depicted), designed to influence the direction(unmarked) in which the designated cleaning fluid 64 leaves the cleaningfluid distribution system 60.

Preferably, the nozzle 70, 72, 74, 76 a, 76 b, 78 a, 78 b exhibitsfurther actuating means (not depicted), designed to influence thecharacteristic (not depicted) with which the designated cleaning fluid64 leaves the cleaning fluid distribution system 60, preferably thespeed of the designated cleaning fluid (not depicted).

The electronic components of a cleaning system 16 preferably include anelectronic control unit 18 and/or a data processing system (notdepicted), whereby a preferentially included data processing system (notdepicted) is preferably integrated into the electronic control unit 18.

Preferably, the electronic control unit 18 is equipped with allstructural electronic elements (not depicted) required for thecompletion of the cleaning method (not depicted) presented here.

Preferably, the electronic control unit 18 is electronically connectedto the cleaning fluid distribution system 60 by means of an electricalconnection (not depicted).

The electronic control unit 18 is preferably set up to control and/orregulate a cleaning process (not depicted) using the cleaning system 16for surface 20, 22, 24, 26, 28 to be cleaned.

The motor vehicle 14 preferably exhibits one or more sensors 50, 52 inthe front apron of the motor vehicle 14 whose one or more associatedsurfaces 20, 22 to be cleaned preferably represent a surface section(unmarked) of the motor vehicle 14. For cleaning the correspondingsurfaces 20, 22, the cleaning system 16 is preferably arranged so thatthe designated cleaning fluid 64 is conveyed during the cleaning process(not depicted) through the associated nozzles 70, 72 onto the surfaces20, 22 to be cleaned of the sensors 50, 52, whereby the designatedcleaning fluid 64 can be brought into operative connection with thesurfaces 20, 22 to be cleaned. The cleaning fluid 64 is preferablypumped from the cleaning fluid reservoir 62 through the correspondingcleaning fluid line 80 to the nozzles 70, 72, whereby a plurality ofnozzles 70, 72 can be supplied with the designated cleaning fluid 64preferentially through a single cleaning fluid line 80.

Also preferred is a plurality of nozzles 74, 76 a, 76 b which can alsobe supplied by a plurality of corresponding cleaning fluid lines 86, 84,82.

In addition, the motor vehicle 14 preferably exhibits one or moresensors 54 in the rear apron of the motor vehicle 14. To clean thecorresponding surface 24, the cleaning system 16 is designed so that thedesignated cleaning fluid 64 is conveyed during the cleaning process(not depicted) through the associated nozzle 74 to the surface to becleaned 24 of the sensor 54, whereby the designated cleaning fluid 64can be brought into an effective connection with the surface to becleaned 24.

Other surfaces 26, 28 to be cleaned are preferably a windscreen(unmarked) and a rear window (unmarked) of the motor vehicle 14.

Preferably, a sensor 56 is arranged behind the windscreen (unmarked)and/or a sensor 58 behind the rear window (unmarked) of the motorvehicle 14, so that the respective windscreens (unmarked) can alsorepresent the surfaces 26, 28 to be cleaned associated with therespective sensors 56, 58.

A sensor 50, 52, 54, 56, 58, preferably the sensor 56, can preferablyhave several different partial sensors (not depicted), whose commonsurface to be cleaned 26 is the windscreen (unmarked).

In addition to the nozzles 76 a, 76 b, which are connected to thecleaning fluid reservoir 62 by means of the corresponding cleaning fluidlines 84, 82, the cleaning system 16 is equipped with the wipingelements 90, 92 for cleaning the surface 26.

The wiping elements 90, 92 are preferably equipped to remove adesignated cleaning fluid 64 and any dirt (not depicted) from thewindscreen (unmarked) by means of a wiping movement (not depicted).

With the cleaning means 76 a, 76 b, 64, 62, 82, 84, 90, 92 of thecleaning system 16 the surface 26 of the windscreen (unmarked) can becleaned, which partly also represents the surface to be cleaned for thesensor 56.

Preferably, the rear window (unmarked) also exhibits a wiping element 94next to the nozzles 78 a, 78 b, which are preferably connected to thecleaning fluid reservoir 62 together by means of the cleaning fluid line88.

The sensors 50, 52, 54, 56, 58 are electronically connected to theelectronic control unit 18, to transmit the respective values (notdepicted) of the measured quantities 100, 102, 104, 106, 108 from thesensors 50, 52, 54, 56, 58 to the electronic control unit 18.

Among other things, it is conceivable that the electronic control unit18 is an electronic control unit of the cleaning system 16.

The electronic connection between a sensor 50, 52, 54, 56, 58 and theelectronic control unit 18 can also preferably be wireless.

The electronic control unit 18 is preferably set up to carry out thecleaning method (not depicted), particularly preferably a cleaningmethod (not depicted) according to the first aspect of the invention.

The electronic control unit 18 is preferably set up to carry out amethod for indirectly des riving a systematic dependence (not depicted),preferably a systematic dependence (not depicted) for a system behaviour(not depicted) of a cleaning system 16 of a motor vehicle 14,particularly preferably for a system behaviour (not depicted) of acleaning process (not depicted) of a surface 20, 22, 24, 26, 28 of themotor vehicle 14, particularly preferably a method for indirectlyderiving a systematic dependence (not depicted) according to the secondaspect of the invention.

The electronic control unit 18 is preferably set up to carry out amethod for indirectly deriving a systematic dependence (not depicted)for a system behaviour (not depicted) of a system component (notdepicted) of a cleaning system 16 of a motor vehicle 14, particularlypreferably a method for indirectly deriving a systematic dependence (notdepicted) according to the fifth aspect of the invention.

The electronic control unit 18 is preferably set up to carry out amethod for indirectly deriving a systematic dependence (not depicted)for a system behaviour (not depicted) of a soiling process (notdepicted) of a surface 20, 22, 24, 26, 28 of a motor vehicle 14,particularly preferably a method for indirectly deriving a systematicdependence (not depicted) according to the ninth aspect of theinvention.

The electronic control unit 18 is preferably set up to carry out amethod for optimizing a resource requirement (not depicted) for acleaning process (not depicted) of a surface 20, 22, 24, 26, 28 of amotor vehicle 14, particularly preferably a method for optimizing aresource requirement (not depicted) according to a first and/or secondalternative of the third aspect of the invention.

The electronic control unit 18 is preferably set up to carry out amethod for determining a cleaning strategy (not depicted) for cleaning asurface 20, 22, 24, 26, 28 to be cleaned of a motor vehicle 14,particularly preferably a method for determining a cleaning strategy(not depicted) according to the fourth aspect of the invention.

The electronic control unit 18 is preferably set up to carry out amethod for diagnosing a deviation (not depicted) between an actualsystem behaviour (not depicted) and an expected system behaviour (notdepicted) of a system component (not depicted) of a cleaning system 16of a motor vehicle 14, particularly preferably a method for diagnosing adeviation (not depicted) between an actual system behaviour (notdepicted) and an expected system behaviour (not depicted) according to asixth aspect of the invention.

The electronic control unit 18 is preferably set up to carry out amethod for selecting a resolution strategy (not depicted), particularlypreferably a method for selecting a resolution strategy (not depicted)according to the seventh aspect of the invention.

The electronic control unit 18 is preferably set up to use a selectedresolution strategy (not depicted), particularly preferably to use aselected resolution strategy (not depicted) according to the eighthaspect of the invention.

The electronic control unit 18 is preferably set up to use a dependencytable (not depicted) and/or a systematic dependence (not depicted) todetermine an expected availability (not depicted) at a distance (notdepicted) or an operating time (not depicted) of the motor vehicle 14yet to be covered, particularly preferably to use a dependency table(not depicted) and/or a systematic dependence (not depicted) accordingto the tenth aspect of the invention.

The electronic control unit 18 is preferably set up to use a dependencytable (not depicted) and/or a systematic dependence (not depicted) todetermine an expected distance (not depicted) or an operating time (notdepicted) of the motor vehicle 14 yet to be covered when reaching athreshold of availability (not depicted), particularly preferably to usea dependency table (not depicted) and/or a systematic dependence (notdepicted) according to the eleventh aspect of the invention.

The electronic control unit 18 is preferably set up to use a dependencytable (not depicted) and/or a systematic dependence (not depicted) foroptimizing a resource requirement (not depicted) for a cleaning process(not depicted) of a surface 20, 22, 24, 26, 28 of a motor vehicle 14,particularly preferably to use a dependency table (not depicted) and/ora systematic dependence (not depicted) according to the twelfth aspectof the invention.

The electronic control unit 18 is preferably set up to use a dependencytable (not depicted) and/or a systematic dependence (not depicted) todetermine a cleaning strategy (not depicted) for cleaning a surface 20,22, 24, 26, 28 to be cleaned of a motor vehicle 14, particularlypreferably to use a dependency table (not depicted) and/or a systematicdependence (not depicted) according to the thirteenth aspect of theinvention.

The electronic control unit 18 is preferably set up to use a dependencytable (not depicted) and/or a systematic dependence (not depicted) todetermine a necessary expected gain in availability (not depicted),particularly preferably to use a dependency table (not depicted) and/ora systematic dependence (not depicted) according to the fourteenthaspect of the invention.

The electronic control unit 18 is preferably set up to use a systematicdependence (not depicted) derived by a method for indirectly deriving asystematic dependence (not depicted) for a resource efficient cleaningof at least one surface 20, 22, 24, 26, 28 of a motor vehicle 14,particularly preferably to use a systematic dependence (not depicted)according to the fifteenth aspect of the invention.

The electronic control unit 18 is preferably set up to use a controlquantity setpoint (not depicted) derived by a method for optimizing aresource requirement (not depicted) for a cleaning process (notdepicted) of a surface 20, 22, 24, 26, 28 of a motor vehicle 14 for aresource efficient cleaning (not depicted) of at least one surface 20,22, 24, 26, 28 of a motor vehicle 14, particularly preferably to use acontrol quantity setpoint (not depicted) according to the fifteenthaspect of the invention, described here.

The electronic control unit 18 is preferably set up to use a cleaningstrategy (not depicted) derived by a method for determining a cleaningstrategy (not depicted) for cleaning a surface 20, 22, 24, 26, 28 to becleaned of a motor vehicle 14, for a resource efficient cleaning of atleast one surface 20, 22, 24, 26, 28 of a motor vehicle 14, particularlypreferably to use a cleaning strategy (not depicted) according to thefifteenth aspect of the invention, described here.

The electronic control unit 18 is preferably set up to be part of acleaning system 16 according to the sixteenth aspect of the invention,and/or to be part of a motor vehicle 14 according to the seventeenthaspect of the invention, described here.

It should be expressly pointed out that the cleaning system 16 in FIG. 1, which works with a cleaning fluid 64 in the liquid state, can becombined without restriction and advantageously with a cleaning system16 in FIG. 8 , which uses an air jet cleaning.

The cleaning method 10 in FIG. 2 exhibits a sequence of multiplecleaning processes 30, 32, 34, 36, 38, 40 for a plurality of surfaces20, 22, 24 to be cleaned as a function of a course of time 12.

Each cleaning operation 30, 32, 34, 36, 38, 40 necessitates a resourcerequirement 30 d, 32 d, 34 d, 36 d, 38 d, 40 d.

A resource requirement 30 d, 32 d, 34 d, 36 d, 38 d, 40 d may preferablyinclude a required amount of cleaning fluid (not depicted) and/or arequired amount of energy (not depicted) and/or a required amount ofdetergent (not depicted) and/or the like.

Each cleaning process 30, 32, 34, 36, 38, 40 exhibits a cleaning period38 a, 40 a in which at least one cleaning means (not depicted) isbrought into operative connection with the corresponding surface 20, 22,24, whereby each cleaning period 38 a, 40 a exhibits a start time 38 b,40 b and an end time 38 c, 40 c.

In the course of time 12 of a cleaning method 10 a surface 20, 22, 24,26, 28 can be cleaned by a number of cleaning processes 30, 32, 34, 36,38, 40.

Preferably a surface 20, 22, 24, 26, 28, preferably surface 22, iscleaned once during the course of time 12 in the course of a cleaningprocess 30, 32, 34, 36, 38, 40, preferably cleaning process 36.

It is also conceivable that a surface 20, 22, 24, 26, 28, preferablysurface 24, may be cleaned twice during the course of time 12 within theframework of a cleaning process 30, 32, 34, 36, 38, 40, preferablycleaning process 38, 40.

Furthermore, it is also conceivable that a surface 20, 22, 24, 26, 28,preferably surface 20, is cleaned three times during the course of time12 within the scope of a cleaning process 30, 32, 34, 36, 38, 40,preferably cleaning process 30, 32, 34.

In concrete terms, it is conceivable, among other things, that thecleaning process 30 should achieve a certain target value (not depicted)within the scope of the cleaning method 10, that an availability (notdepicted) of a sensor (not depicted) influenced by the surface 20 shouldreach a certain target value (not depicted), and after completion of thecleaning process 30 it was determined that the desired availability (notdepicted) was not achieved, whereupon a further cleaning process 30, 32,34, 36, 38, 40, preferably the cleaning process 32, was started shortlyafter the end (unmarked) of the cleaning process 30.

Furthermore, a further cleaning of surface 20 may be necessary after acertain period (not depicted) of use of the vehicle (not depicted). Thiscleaning requirement (not depicted) is preferably met by means of thecleaning process 34.

The subtraction procedure (unmarked) in FIG. 3 determines a difference100D, 102D, 104D, 106D, 108D from the measured values 100 b, 100 c, 102b, 102 c, 104 b, 104 c, 106 b, 106 c, 108 b, 108 c of a measuredquantity (unmarked) at end time 100 c, 102 c, 104 c, 106 c, 108 c and atstart time 100 b, 102 b, 104 b, 106 b, 108 b of cleaning period (notdepicted).

Preferred is the measured quantity (unmarked) an availability (notdepicted) of a sensor (not depicted), whereby from a value ofavailability 100 c, 102 c, 104 c, 106 c, 108 c at the end of a cleaningprocess a value of availability 100 b, 102 b, 104 b, 106 b, 108 b at thebeginning of this cleaning process (not depicted) is subtracted in orderto arrive at the difference in availability 100D, 102D, 104D, 106D,108D, preferred the value of availability 100 b of one sensor (notdepicted) at the beginning of the cleaning process (not depicted) forthis sensor (not depicted) is subtracted from the value of availability100 c of a sensor (not depicted) at the end of a cleaning process (notdepicted) in order to arrive at the difference in availability 100D ofthis sensor (not depicted).

A systematic dependence 120, 120D, 120R between values (unmarked) ofquantities 100D, 102D, 104D, 106D, 108D, 110, 111, 112, 112, 114, 115,116, 117, 118, 119, 30 d, 32 d, 34 d, 36 d, 38 d, 40 d in FIG. 4 is asystematic dependence 120, 120D, 120R between values (unmarked) of aninput quantity 110, 111, 112, 112, 114, 115, 116, 117, 118, 119 of asystem (not depicted) and values (unmarked) of an output quantity 100D,102D, 104D, 106D, 108D, 30 d, 32 d, 34 d, 36 d, 38 d, 40 d of a system(not depicted).

Preferred is the input quantity 110, 111, 112, 112, 114, 115, 116, 117,118, 119 of the system (not depicted) a measured quantity, preferred acontrol quantity 110, 111, 112, 112, 114, 115, 116, 117, 118, 119 of thesystem, especially preferred a single control quantity 110 of thesystem.

Preferred is the output quantity 100D, 102D, 104D, 106D, 108D, 30 d, 32d, 34 d, 36 d, 38 d, 40 d of the system (not depicted) a measuredquantity, preferred an availability of a sensor, especially preferredthe difference of the availability of a sensor 100D, 102D, 104D, 106D,108D, which is determined by subtraction of the availability of thesensor (not depicted) at the beginning of the cleaning process (notdepicted) from the value of availability of a sensor (not depicted) atthe end of a cleaning process (not depicted).

Furthermore preferred, the output quantity 100D, 102D, 104D, 106D, 108D,30 d, 32 d, 34 d, 36 d, 38 d, 40 d of the system (not depicted) is as aresource requirement 30 d, 32 d, 34 d, 36 d, 38 d, 40 d for theaccomplishment of a cleaning process (not depicted).

A preferred systematic dependence 120D is a systematic dependencebetween the measured values (unmarked) of a control quantity 110, 111,112, 112, 114, 115, 116, 117, 118, 119 of the system (not depicted),preferably one control quantity 110 of the system (not depicted), andthe difference between measured values of a measured quantity at endtime and at start time of a cleaning process 100D, 102D, 104D, 106D,108D, preferably the difference between measured values of one measuredquantity at end time and at start time of a cleaning process 100D.

A preferred systematic dependence 120R is a systematic dependencebetween the measured values (unmarked) of a control quantity 110, 111,112, 112, 114, 115, 116, 117, 118, 119 of the system (not depicted),preferably one control quantity 110 of the system (not depicted), andthe a resource requirement 30 d, 32 d, 34 d, 36 d, 38 d, 40 d,preferably the resource requirement 30 d for the accomplishment of onecleaning process (not depicted).

A cleaning device 11 in FIG. 5 for a cleaning, preferably a resourceefficient cleaning, particularly preferred a resource-saving cleaning,of at least one surface (not depicted) of a motor vehicle (not depicted)consists of a plurality of sensors 50, 56 a, 56 b, a cleaning system 16,an electronic data processing and evaluation system 152, a database 154,a control quantity acquisition and setting system 156, a processquantity acquisition system 158 and a measured quantity acquisitionsystem 160, among other components (not depicted).

The electronic data processing and evaluation system 152 is connected tothe database 154 via the data link 194 for data exchange.

Furthermore, the electronic data processing and evaluation system 152 isconnected for data exchange to the process quantity acquisition system158 via the data link 195, to the control quantity acquisition andsetting system 156 via the data link 193, and to the measured quantityacquisition system 160 via the data link 192.

Preferably, the electronic data processing and evaluation system 152,the database 154, the control quantity acquisition and setting system156, the process quantity acquisition system 158 and the measuredquantity acquisition system 160 together form the data processing system150.

The electronic data processing and evaluation system 152 is set up forcarrying out a procedure according to the first, second, third, fourth,fifth, sixth, seventh and/or eighth aspect of the invention.

The cleaning system 16 exhibits the control quantities 110, 112, 114 andthe process quantities 140, 141, 142, which are system related processquantities 143. With the control quantity 114 the wiping element 90, 92can be controlled and/or regulated.

It should be noted that the cleaning system 16 may also have more orless than the specified control quantities 110, 112, 114 and also moreor less than the specified process quantities 140, 141, 142. The numberof control quantities 110, 112, 114 and process quantities 140, 141, 142chosen here is to be understood as a schematic example.

For the cleaning process (not depicted) with the cleaning device 11,there are also the further process quantities 145, 146, 147 relevant,whereby these are to be understood as environmental process quantities144 and whereby their number is also to be understood in the sense of aschematic example.

For example, environmental process quantities 144 can be air temperature145, humidity 146 and air pressure 147. It goes without saying that thenumber of environmental process quantities 144 selected here in thecontext of the cleaning system 16 is to be understood as a schematicexample.

The vehicle (not depicted) has the sensors 50, 56 a, 56 b, whereby it isexpressly pointed out that the number of sensors 50, 56 a, 56 b is to beunderstood in the sense of a schematic example.

Preferred is the surface to be cleaned with the sensors 56 a, 56 bcorresponding to the surface 26.

Also preferred is the surface to be cleaned corresponding to sensor 50,surface 20.

The measured quantity 106, preferably the availability of the sensor 56a, is determines with the sensor 56 a, which is connected to themeasured quantity acquisition system 160 for data exchange via data link188.

The measured quantity 107, preferably the availability of the sensor 56b, is determines with the sensor 56 b, which is connected to themeasured quantity acquisition system 160 for data exchange via data link187.

The measured quantity 100, preferably the availability of the sensor 50,is determines with the sensor 50, which is connected to the measuredquantity acquisition system 160 for data exchange via data link 186.

If required, the measured quantity acquisition system 160 controls thesensors 50, 56 a, 56 b, supplies them with energy if required, digitizesthe data arriving via the data links 186, 187, 188 if required,determines the availability of the corresponding sensors 50, 56 a, 56 bat a fixed point in time if required, which is preferably preferred bythe electronic data processing and evaluation system 152 and forwardsthis data to the electronic data processing and evaluation system 152via the data link 192 if preferred.

The actual value of the control quantity 110 is determined with thepreferred combined control quantity sensor and control quantitytransmitter 130, which is connected to the control quantity acquisitionand setting system 156 for data exchange via the data link 189.

The actual value of the control quantity 112 is determined with thepreferred combined control quantity sensor and control quantitytransmitter 132, which is connected to the control quantity acquisitionand setting system 156 for data exchange via the data link 190.

The actual value of the control quantity 114 is determined with thepreferred combined control quantity sensor and control quantitytransmitter 134, which is connected to the control quantity acquisitionand setting system 156 for data exchange via the data link 191.

If required, the control quantity acquisition and setting system 156controls the optional combined control quantity sensors and controlquantity transmitters 130, 132, 134 if required, supplies them withenergy if required, digitizes the incoming data via the data connections189, 190, 191 if required, determines the actual values of the controlquantities 110, 112, 114 at a fixed point in time if required, which ispreferably preferred by the electronic data processing and evaluationsystem 152 and forwards this data to the electronic data processing andevaluation system 152 via the data link 192 if preferred.

The actual value of the process quantity 140 is determined with theprocess quantity sensor 170, which is connected to the process quantityacquisition system 158 for data exchange via the data link 196.

The actual value of the process quantity 141 is determined with theprocess quantity sensor 171, which is connected to the process quantityacquisition system 158 for data exchange via the data link 197.

The actual value of the process quantity 142 is determined with theprocess quantity sensor 172, which is connected to the process quantityacquisition system 158 for data exchange via the data link 198.

The actual value of the process quantity 145 is determined with theprocess quantity sensor 175, which is connected to the process quantityacquisition system 158 for data exchange via the data link 183.

The actual value of the process quantity 146 is determined with theprocess quantity sensor 176, which is connected to the process quantityacquisition system 158 for data exchange via the data link 184.

The actual value of the process quantity 147 is determined with theprocess quantity sensor 177, which is connected to the process quantityacquisition system 158 for data exchange via the data link 185.

If required, the process quantity acquisition system 158 controls theprocess quantity sensors 170, 171, 172, 175, 176, 177, supplies themwith energy if required, digitizes the data arriving via the data links183, 184, 185, 196, 197, 198 if required, determines the actual valuesof the process quantities 140, 141, 142, 145, 146, 147 at a fixed pointin time if required, which is preferably preferred by the electronicdata processing and evaluation system 152 and forwards this data to theelectronic data processing and evaluation system 152 via the data link195 if preferred.

Among other tasks, the electronic data processing and evaluation system152 takes over the control and/or regulation of the control quantities110, 112, 114 of the cleaning system 16 and thus preferably the controland/or regulation of the cleaning method (not depicted). The cleaning ofat least one surface 20, 26 of a motor vehicle (not depicted) preferablyshould be controlled and/or regulated taking into account the processquantities 140, 141, 142, 145, 146, 147 preferably resource efficient,particularly preferably resource-saving.

Such control and/or regulation of the cleaning system 16 is achieved byadjusting the setpoints of the control quantities 110, 112, 114 via thepreferably combined control quantity sensors and control quantitytransmitters 130, 132, 134, for which purpose the preferably combinedcontrol quantity sensors and control quantity transmitters 130, 132, 134are connected to the electronic data processing and evaluation system152 via the data links 180, 181, 182.

It should be noted that all data links 180, 181, 182, 183, 184, 185,186, 187, 188, 189, 190, 191, 192, 193, 194, 195, 196, 197, 198 maypreferably be wireless, whereby the corresponding data may betransmitted wirelessly from the associated sensors to the dataprocessing system 150.

The data processing system 150 in FIG. 6 for a cleaning system (notdepicted) for cleaning at least one surface (not depicted) of a motorvehicle (not depicted), comprising a database 154, a measured quantityacquisition system 160 for determining a value of a measured quantity,preferably a difference between a measured value of a measured quantityat an end time and at a start time of a cleaning period 100D, 102D, 104D106D, particularly preferred a difference between an availability of thesensor (not depicted) at an end time and at a start time of a cleaningperiod 100D, 102D, 104D 106D, a control quantity acquisition and settingsystem 156 for monitoring, recording and adjusting a control quantity110, 112, 114 and an electronic data processing and evaluation system152.

The control quantity acquisition and setting system 156 is connected tothe cleaning system (not depicted) and controls and/or regulates acleaning process (not depicted) of a surface to be cleaned (notdepicted) or a cleaning method (not depicted). The points shown in thedata element of the control quantity acquisition and setting system 156show that there may be a large number of control quantities (notdepicted) in addition to control quantities 110, 112, 114.

The recorded data of the control quantity acquisition and setting system156 are forwarded to the database 154.

The measured quantity acquisition system 160 determines from themeasured value of the measured quantity at the start time of thecleaning period 100 b, 102 b, 104 b, 106 b and the measured value of themeasured quantity at the end time of the cleaning period 100 c, 102 c,104 c, 106 c the difference between a measured value of a measuredquantity at an end time and at a start time of a cleaning period 100D,102D, 104D 106D, particularly preferred a difference between anavailability of the sensor (not depicted) at an end time and at a starttime of a cleaning period 100D, 102D, 104D 106D. The points shown in thedata element of the measured quantity acquisition and setting system 156show that there may be a large number of measured quantities (notdepicted) in addition to measured quantities having the values 100D,102D, 104D 106D.

The recorded data of the measured quantity acquisition system 160 areforwarded to the database 154.

Database 154 assigns the data and assigns them to data sets DP1, DP2,DP3, DP4 with reference to each other. These data sets DP1, DP2, DP3,DP4 are stored by the database 154 in a dependency table DT, preferablystored chronologically in the dependency table DT.

The electronic data processing and evaluation system 152 can assess thedata sets DP1, DP2, DP3, DP4 within the dependency table (DT) of thedatabase 154.

The electronic data processing and evaluation system 152 uses the datasets DP1, DP2, DP3, DP4 in the dependency table (DT) of the database 154preferably to derive a systematic dependence between the inputquantities and the output quantities of the cleaning system (notdepicted), preferably between the control quantities 110, 112, 114 andthe difference between an availability of the sensor (not depicted) atan end time and at a start time of a cleaning period 100D, 102D, 104D106D.

The resulting systematic dependence is also stored in database 154 (notdepicted).

Preferably, the electronic data processing and evaluation system 152 ispart of the data processing system 150, which is preferably a part ofthe electronic control unit 18.

The system 200 in FIG. 7 , preferably the cleaning system (unmarked),exhibits at least one input quantity 202 and at least one outputquantity 204, whereby the output quantity 204 depends on the inputquantity 202 by means of the system behaviour (not depicted) of thesystem 200.

Preferably the system 200, preferably the cleaning system (unmarked),exhibits as an input quantity 202 at least one control quantity 110,111, 112 and/or at least one data representing measured quantity 210,212, 214.

Preferably the system 200, preferably the cleaning system (unmarked),exhibits as an output quantity 204 at least one system related measuredquantity 140, 141, 142 and/or at least one resource requirement 30 d, 32d, 34 d of a cleaning process (not depicted) of a surface to be cleaned(not depicted) and/or at least one availability 220, 222, 224 of asensor (not depicted).

The motor vehicle 14 in FIG. 8 is equipped with a cleaning system 16,which is based on air jet cleaning. The cleaning system 16 essentiallyconsists of a cleaning fluid pump 66, an air pressure reservoir 68, acleaning fluid distribution system (unmarked) and at least one nozzle70, 72, 74, 76 a, 78.

The cleaning fluid distribution system (unmarked) consists essentiallyof at least one fluid line 80, 82, 84, 86, 88, at least one cleaningfluid valve 230, 232, 234, 236, 238 and at least one nozzle (70, 72, 74,76, 78).

The cleaning fluid pump 66 is designed to draw air as designatedcleaning fluid (not depicted) from the environment, compress it and pumpit into the air pressure reservoir 68.

If no cleaning fluid valve 230, 232, 234, 236, 238 is open, the cleaningfluid pump 66 is designed to increase the pressure (not depicted) in theair pressure reservoir 68 until a system pressure is reached.

The nozzle 70, 72, 74, 76, 78 is a device through which the pressurizedair (not depicted) can leave the cleaning system 16 and which isdesigned to bring the pressurized air (not depicted) into aninteraction, preferably an operative connection, with the surface 20,22, 24, 26, 28 to be cleaned.

Preferably the nozzle 70, 72, 74, 76, 78 is a device designed to controla direction (unmarked) or a characteristics (not depicted) of thedesignated pressurized air (not depicted) as it exits the cleaning fluiddistribution system 60.

Preferably, the nozzle 70, 72, 74, 76, 78 exhibits actuating means (notdepicted), designed to influence the direction (unmarked) in which thedesignated pressurized air (not depicted) leaves the cleaning fluiddistribution system 60.

Preferably, the nozzle 70, 72, 74, 76, 78 exhibits further actuatingmeans (not depicted), designed to influence the characteristic (notdepicted) with which the designated pressurized air (not depicted)leaves the cleaning fluid distribution system 60, preferably the speedof the designated pressurized air (not depicted).

The electronic components (not depicted) of a cleaning system 16preferably include an electronic control unit (not depicted) and/or adata processing system (not depicted), whereby a preferentially includeddata processing system (not depicted) is preferably integrated into theelectronic control unit (not depicted).

Preferably, the electronic control unit (not depicted) is equipped withall structural electronic elements (not depicted) required for theexecution of the cleaning method (not depicted) presented here.

Preferably, the electronic control unit (not depicted) is electronicallyconnected to the cleaning fluid distribution system 60 by means of anelectrical connection (not depicted), preferably electronicallyconnected to the at least one cleaning fluid valve 230, 232, 234, 236,238.

The electronic control unit (not depicted) is preferably set up tocontrol and/or regulate a cleaning process (not depicted) using thecleaning system 16 for surface 20, 22, 24, 26, 28 to be cleaned.

The motor vehicle 14 preferably exhibits one or more sensors 50 in thefront apron of the motor vehicle 14 whose associated surface 20 to becleaned preferably represents a surface section (unmarked) of the motorvehicle 14. For cleaning the corresponding surface 20, the cleaningsystem 16 is preferably arranged so that the designated pressurized airis conveyed during the cleaning process (not depicted) through theassociated nozzle 70 onto the surfaces 20 to be cleaned of the sensors50, whereby the designated pressurized air can be brought into operativeconnection with the surfaces 20 to be cleaned. The pressurized air (notdepicted) is preferably pumped from the air pressure reservoir 68through the corresponding cleaning fluid line 80 to the nozzle 70.

In addition, the motor vehicle 14 preferably exhibits one or moresensors 52 in the rear apron of the motor vehicle 14. To clean thecorresponding surface 22, the cleaning system 16 is designed so that thedesignated pressurized air (not depicted) is conveyed during thecleaning process (not depicted) through the associated nozzle 72 to thesurface to be cleaned 22 of the sensor 52, whereby the designatedpressurized air (not depicted) can be brought into an effectiveconnection with the surface to be cleaned 22.

Other surfaces 24, 26, 28 to be cleaned are preferably a part of theleft and right exterior rear-view mirrors (unmarked) and the rear window(unmarked) of the motor vehicle 14.

The surface 26, 28 to be cleaned in an rear-view mirror (unmarked) ispreferably divided into a first partial surface (not depicted), which isassigned to a camera for recording the not depicted side mirror image,and a second partial surface (not depicted), which is assigned to acamera for recording the not depicted vehicle side line.

A cleaning system 16, which is based on air jet cleaning, is preferablydesigned to remove impurities from the surface to be cleaned (20, 22,24, 26, 28) with a liquid (not depicted).

It should be expressly pointed out that the cleaning system 16 in FIG. 8, which uses an air jet cleaning system, can be combined withoutrestriction and advantageously with a cleaning system 16 in FIG. 1 ,which works with a cleaning fluid 64 in the liquid aggregate state.

Specifically, a combination of a conventional cleaning system 16 with acleaning system 16 on the basis of an air jet cleaning is considered,wherein the conventional cleaning system 16 applies a cleaning liquid(not depicted) in a liquid aggregate state to the surface to be cleaned20, 22, 24, 26, 28 and the cleaning system 16 on the basis of an air jetcleaning subsequently applies the cleaning liquid (not depicted) in aliquid aggregate state by means of a cleaning liquid (not depicted) ingaseous aggregate state, in particular by means of the pressurized air(not depicted), so that impurities are first softened by a cleaningliquid (not depicted) in a liquid state of aggregation and then removedby a cleaning liquid (not depicted) in a gaseous state of aggregationtogether with the cleaning liquid (not depicted) in a liquid state ofaggregation from the surface 20, 22, 24, 26, 28 to be cleaned.

The motor vehicle 14 in FIG. 9 is equipped with a cleaning system 16exhibits several nozzles (unmarked) for several surfaces to be cleaned20, 22, 24, 26, 28 (further surfaces to be cleaned are unmarked).

The cleaning fluid distribution system (unmarked) is preferablyunderstood as a system designed to provide a designated cleaning fluid64 from a cleaning fluid reservoir 62, which is designed to store thedesignated cleaning fluid 64, preferably by means of at least onecleaning fluid line (unmarked), designed to guide the designatedcleaning fluid 64, and at least one nozzle (unmarked) on a surface 20,22, 24, 26, 28 (further surfaces to be cleaned are unmarked) of a motorvehicle 14 to be cleaned.

Preferably a cleaning fluid distribution system (unmarked) is equippedwith at least one cleaning fluid pump 66, which is designed to pump thedesignated cleaning fluid 64, and which is preferably integrated intothe cleaning fluid reservoir 62.

The cleaning fluid system 16 of them motor vehicle 14 in FIG. 9 exhibitsfive cleaning fluid pumps 66, of which two pieces are designed ascleaning fluid dual pumps 66 and three pieces as cleaning fluid monopumps 66.

A cleaning fluid dual pump 66 is designed to simultaneously supply twocleaning fluid lines (unmarked) with cleaning fluid 64.

A cleaning fluid mono pump 66 is designed to supply one cleaning fluidline (unmarked) with cleaning fluid 64 at a time.

The five cleaning fluid pumps 66 are integrated into the cleaning fluidreservoir 62.

The cleaning fluid reservoir has a cleaning fluid reservoir level sensor63, which is designed to measure the level of the cleaning fluidreservoir 62 and, if necessary, to pass it on to the electronic controlunit (not depicted).

The motor vehicle 14 has a sensor 50 in the front apron of the vehicle,which is designed as a light detection and ranging sensor (lidar). Thesensor 50 is functionally related to the surface 20. If the surface 20is dirty, the functionality of the sensor 50 may be limited. If thesurface 20 is particularly dirty, it is even possible that the sensor 50is no longer functional.

The surface 20, which is in an effective connection with the sensor 50,is still in an effective connection with at least one nozzle (unmarked),which is designed to bring a cleaning fluid 64 into an effectiveconnection with the surface 20. In other words, the at least one nozzle(unmarked) is designed to apply the cleaning fluid 64 to the surface 20to be cleaned so that the contamination of the surface 20 can be reducedand the functionality of the associated sensor 50 can be improved.

Furthermore, the motor vehicle 14 exhibits at least one nozzle(unmarked) at each of the front headlights (unmarked), which is adaptedto apply the cleaning fluid 64 to each of the front headlights(unmarked).

The nozzles (unmarked) assigned to the headlights (unmarked) and thelidar 50 are each connected to a cleaning fluid multi way valve 242 viaa cleaning fluid line (unmarked).

The cleaning fluid multi way valve 242 can be controlled by theelectronic control unit (not depicted) and, according to aspecification, release or prevent the passing on of the cleaning fluid64 to the nozzles (unmarked) assigned to the headlights (unmarked) andthe lidar 50 by means of a control quantity setpoint (not depicted).

It is understood that with a cleaning fluid multi way valve 240, 242 itis intended that such a multi way valve is designed to supply at leasttwo, three, four, five, six, seven, eight or more nozzles separatelyand/or sequentially and/or parallel and/or simultaneously with cleaningfluid 64.

In this case, the cleaning fluid multi way valve 242 is also connectedto nozzles (unmarked), which are operatively connected to the windscreenof the motor vehicle 14, so that the cleaning fluid multi way valve 242can enable or disable the supply of cleaning fluid 64 to the windscreen.

The cleaning fluid multi way valve 242 is connected via a cleaning fluidline (unmarked) to one of the cleaning fluid mono pumps 66, which isequipped to convey the cleaning fluid 64 to the cleaning fluid multi wayvalve 242.

It is understood that the cleaning fluid multi way valve 242 in adifferent embodiment could alternatively be supplied with a cleaningfluid dual pump 66.

The rear window (unmarked) of the motor vehicle 14 is supplied withcleaning fluid 64 via a cleaning fluid mono pump 66 connected to thecleaning fluid reservoir 62, a corresponding cleaning fluid line(unmarked) and two nozzles (unmarked).

Cleaning fluid 64 is thereby brought into an active connection with therear window (unmarked) of the motor vehicle 14 when the associatedcleaning fluid pump 66 is supplied with electrical energy and thusstarts the delivery operation of cleaning fluid 64 from the cleaningfluid reservoir 62.

In each case one cleaning fluid dual pump 66 is operatively connected toa sensor 56, 58 and the associated surfaces 26, 28 to be cleaned.Furthermore, each of these cleaning fluid dual pumps 66 is alsooperatively connected to at least one nozzle (unmarked) in each case,which in turn is operatively connected to a respective side mirror(unmarked) of the motor vehicle 14. Each of the cleaning fluid dualpumps 66 supplies one side of the motor vehicle 14.

The sensors 56, 58 are preferably also designed as lidar sensors 56, 58.

In addition, the motor vehicle 14 has a sensor 54 in the rear apron ofthe motor vehicle 14. The associated surface 24 is in active connectionwith a nozzle (unmarked), which is in active connection with a cleaningfluid mono pump 66 via a cleaning fluid line (unmarked) and a cleaningfluid multi way valve 240.

The cleaning fluid multi way valve 240 is also designed to supply onenozzle (unmarked) with cleaning fluid 64 each, which is in activeconnection with a rear light (unmarked) of the motor vehicle 14.

It is understood that a deviating motor vehicle 14 according to analternative embodiment can have a deviating number of cleaning fluidpumps 66 and a different constellation of cleaning fluid lines(unmarked), nozzles (unmarked) and cleaning fluid multi way valves 240,242.

It should be expressly pointed out that the cleaning system 16 in FIG. 1, which works with a cleaning fluid 64 in the liquid state, can becombined without restriction and advantageously with a cleaning system16 in FIG. 8 , which uses an air jet cleaning.

The method for indirectly deriving a systematic dependence MDSD1 for asystem behaviour of a cleaning system of a motor vehicle, particularlyfor a system behaviour of a cleaning process of a surface to be cleanedof the motor vehicle in FIG. 10 exhibits the steps:

-   -   Build dependency table BDT, and    -   Derive systematic dependence DSD

Preferably, the method for indirectly deriving a systematic dependenceMDSD1 for a system behaviour of a cleaning system concerns cleaning ofat least one surface of the motor vehicle, preferably a resourceefficient cleaning, particularly preferably a resource-saving cleaning.

The derived systematic dependence describes the system behaviour betweenan input quantity of the system and an output quantity of the system.

The step build dependency table BDT exhibits the substeps:

-   -   Determine input quantity as a first parameter by means of at        least one sensor BDTS1;    -   Determine output quantity as a second parameter by means of at        least one sensor BDTS2;    -   Digitalize the determined first and second parameter if        necessary BDTS3;    -   Store the determined first and second parameter in an ordered        manner with reference to one another in the database as a data        set of a dependency table BDTS4; and    -   Repeat the above steps until enough data sets have been        collected.

The method for indirectly deriving a systematic dependence MDSD1 isexecuted by means of a data processing system exhibiting an electronicdata processing and evaluation system and a database.

The step build dependency table BDT is repeated until at least two datasets are present, preferably at least 50 data sets, particularlypreferably at least 200 data sets.

The dependency table created by the step build dependency table BDT isnow used to derive the systematic dependence by means of the step derivesystematic dependence DSD.

The step derive systematic dependence DSD is executed by the electronicdata processing and evaluation unit and exhibits the substeps:

-   -   Access the respective data sets from the dependency table stored        in the database DSDS1; and    -   Determine the systematic dependence from the data sets of the        dependency table by means of an algorithm DSDS2.

Preferably, the derived systematic dependence is then stored by afurther substeb of the step derive systematic dependence DSD in thedatabase and/or the electronic data processing and evaluation unitand/or an electronic control unit DSDS3.

The Method for optimizing a resource requirement MORR for a cleaningprocess of a surface of a motor vehicle in FIG. 11 exhibits the steps:

-   -   Access AD the data of the dependency table or the systematic        dependence from a database and/or an electronic data processing        and evaluation unit and/or an electronic control unit;    -   Derive a difference between the availability of the sensor at an        end time of the cleaning process and the availability of the        sensor at a start time of the cleaning process for each data set        of the dependency table or for a course of the systematic        dependence;    -   Derive DCQSS1 a ratio of that difference to the respective        resource requirement for each data set of the dependency table        or for a course of the systematic dependence;    -   Select DCQSS2 the control quantity of the data set exhibiting        the highest value of that ratio or which belongs to the point in        the course of that ratio exhibiting the highest value of that        ratio; and    -   Store SCQS that control quantity as a control quantity setpoint        in the database and/or the electronic data processing and        evaluation unit and/or the electronic control unit.

It is understood that the above steps can be performed with theappropriate adjustments both for the discrete points given by each dataset of a dependency table and for the courses given by a systematicdependence. In the case of a systematic dependence, the progressions forthe individual variables are also determined and/or taken as a basis forconsideration.

The Method for determining a cleaning strategy for cleaning a surface tobe cleaned of a motor vehicle in FIG. 12 exhibits the steps:

-   -   Check MCSS1 a currently selected cleaning mode 250;    -   Select MCSSS2 a sensor required for the currently selected        cleaning mode 250;    -   Check MCSS3 an actual availability of each selected sensor;    -   Determine MCSS4 a distance which the motor vehicle can still        cover as a function of the current availability of the selected        sensor until an expected availability then reaches a threshold        value at which the surface which is operatively connected to the        associated sensor is to be cleaned; and    -   Determine MCSS5 a control quantity setpoint for resource        efficient, preferably resource-saving, cleaning of each surface        to be cleaned operatively connected to each selected sensor.

The cleaning strategy results from the one control quantity setpoint orthe plurality of control quantity setpoints determined for the one orthe plurality of sensors. The control strategy provides information onthe type of cleaning of each surface to be cleaned according to theselected cleaning mode 250, the sequence of the corresponding cleaning,in particular also the sequence of several sequences for a surface to becleaned, as well as, if necessary, the start time of each individualcleaning process, in particular depending on the actual availability ofthe sensor, which is operatively connected to the corresponding surface.

It should be expressly noted that some of the steps mentioned above canalso be performed in a different order to achieve the same result.

In particular, the step MCSS4 is not essential and only brings anadvantage in the specific execution example if the cleaning strategytakes into account that the beginning of a cleaning process should notstart immediately after, but waits for the achievement of apredetermined actual availability of the sensor.

The MCSS4 step can be performed in particular by applying a method(UEAT) to determine an expected distance or operating time of the motorvehicle yet to be covered when reaching a threshold of availability.

The MCSS4 step can be performed in particular by applying a method MORRfor optimizing a resource requirement for a cleaning process of asurface of a motor vehicle.

The schematically represented course of an availability 220, 222, 224 inFIG. 13 exhibits an actual availability 221, an expected availability223, and an expected gain in availability 229.

Furthermore, the course of the availability 220, 222, 224 exhibits theinterval limits 225 226, which can depend on the individual design ofthe sensor, its installation situation in the broadest sense and otherconditions.

The interval limit 225 indicates that the associated sensor can nolonger fulfill its requirements when the interval limit 225 is reached.If the availability drops further, the associated sensor can also nolonger fulfill its requirements. Before the sensor can at leastpartially meet its requirements again, a surface that is operativelyconnected to the sensor must be cleaned using a cleaning process.

Availability above interval limit 226 indicates that the associatedsensor can fully meet its requirements.

Between the interval limits 225, 226, the associated sensor can at leastpartially meet its requirements.

Furthermore, the course of availability 220, 222, 224 exhibits athreshold of availability 227, 228. If the value falls below such athreshold value, the associated sensor can no longer perform a task thatis related to the respective threshold of availability 227, 228.

Preferably, the threshold of availability 227 refers to a situation inwhich the sensors of the motor vehicle (not depicted) are cleanedaccording to a cleaning mode, which is set up to enable the motorvehicle to have the best possible range, wherein each surfaces which isoperatively connected to the sensor relevant for motor vehicle operationwith the best possible range is to be cleaned when reaching thethreshold of availability 227.

Another preferred threshold of availability 228 refers to a situation inwhich the sensors of the motor vehicle (not depicted) are cleanedaccording to a cleaning mode, which is set up to enable fully autonomousmotor vehicle operation.

The expected availability 223 can be estimated on the basis of theactual availability 221 and depending on the operating conditions of themotor vehicle and the weather situation along the route to be covered bythe motor vehicle using an appropriate procedure, in particular byapplying a method (UEAT) to determine an expected distance or operatingtime of the motor vehicle yet to be covered when reaching a threshold ofavailability.

The expected gain in availability 229 is the expected increase inavailability when performing a cleaning process defined by its controlquantity setpoint.

The schematically represented course of an availability 220, 222, 224 inFIG. 14 during evaluation of a system behaviour of a soiling process ofa surface exhibits a first availability (260), a second availability(262) and a loss of availability (264), wherein the second availability(262) is less than the first availability by a loss of availability(264).

The schematically illustrated procedure (UEA) to determine an expectedavailability (223) at a distance (270) or operating time (280) of themotor vehicle (not depicted) yet to be covered in FIG. 15 is essentiallyillustrated by means of a diagram which shows a course of a systematicdependence (122) for a system behaviour (not depicted) of a soilingprocess (not depicted) in terms of an availability (220, 222, 224)against a distance (270) or operating time (280), wherein the course ofthe availability (220, 222, 224) starts from the actual availability(221).

According to a first step (UEAa) of the method, the course of thesystematic dependence (122) for the system behaviour (not depicted) ofthe soiling process (not depicted) of the respective surface to becleaned (not depicted) up to the distance yet to be covered (272) or theoperating time yet to be covered (282) is tracked.

The functional value of the systematic dependence (122), in particularthe expected availability (223) at the location of the distance yet tobe covered (272) or the operating time yet to be covered (282), isdetermined by means of a second step (UEAb) of the method, in particularby insertion into the systematic dependence (122) or by selection of thenearest empirical value (unmarked) or by linear interpolation betweenthe two nearest empirical values (unmarked).

The schematically illustrated procedure (UEAT) to determine an expecteddistance (274) or an expected operating time (284) of the motor vehicle(not depicted) yet to be covered when reaching a threshold ofavailability (227, 228) in FIG. 16 is essentially illustrated by meansof a diagram which shows a course of a systematic dependence (122) for asystem behaviour (not depicted) of a soiling process (not depicted) interms of an availability (220, 222, 224) against a distance (270) oroperating time (280), wherein the course of the availability (220, 222,224) starts from the actual availability (221).

According to a first step of the method (UEATa) and a second step of themethod (UEATb), the function value of the systematic dependence (122),in particular the threshold of availability (227, 228), is used todetermine the expected distance (274) or the expected operating time(284) yet to be covered when reaching the threshold of availability(227, 228), in particular by equating the systematic dependence (122)with the threshold of availability (227, 228) or by selecting thenearest empirical value (unmarked) or by linear interpolation betweenthe two nearest empirical values (unmarked).

The schematically illustrated procedure (UEGAT) to determine an expectedgain in availability (229), whereby the sum of the actual availability(221) and the expected gain in availability (229) is sufficient toachieve a distance (272) or operating time (282) to be covered by themotor vehicle (not depicted) in such a way that a threshold ofavailability (227, 228) is not exceeded in FIG. 17 is essentiallyillustrated by means of a diagram which shows a course of a systematicdependence (122) for a system behaviour (not depicted) of a soilingprocess (not depicted) in terms of an availability (220, 222, 224)against a distance (270) or operating time (280), wherein the course ofthe availability (220, 222, 224) starts from the actual availability(221).

According to a first step of the method (UEGATa), the systematicdependence (122) is shifted in the direction of the distance (270) oroperating time (280) until the shifted systematic dependence (122)intersects the threshold of availability (227, 228) at the distance(272) or the operating time (282) to be covered.

The expected gain in availability (229) can then be determined from thenew y-axis section (unmarked) by a difference between the new y-axissection (unmarked) and the actual availability (221).

The diagnostic method in FIG. 18 essentially consists of the stepperform diagnostic analysis (unmarked).

The method serves to diagnose a system component (not depicted) of acleaning system (not depicted), in particular an autonomously executableself-diagnosis, which can be started by the cleaning system (notdepicted) via the electronic control unit (not depicted) and/or by thedriver of a motor vehicle (not depicted).

The system behaviour of the system component is considered and evaluatedas an object of the system diagnosis.

Therefore, the expected system behaviour of a system component (notdepicted) of a cleaning system (not depicted) is compared with a systembehaviour measured during the monitoring of this system component (notdepicted). This comparison is carried out on the basis of at least onevalue of an output quantity (not depicted).

If the comparison leads to the result that the monitored systembehaviour of the system component (not depicted) corresponds to theexpected system behaviour, it is concluded that the system component hasno defect and/or no fault and/or the system component is not impaired byexternal influences acting on the system component (not depicted).

In other words, if the system component (not depicted) behaves asexpected regarding the compared at least one output quantity, there isno deviation of the actual system behavior for this system component.

In the other case, i.e. if the monitored system behaviour of the systemcomponent does not correspond to the expected system behaviour, adeviation results which can be further characterized in a preferablydownstream step (not depicted), in particular with a procedure accordingto the sixth aspect of the invention.

If the deviation of the monitored output quantity from the expectedoutput quantity and/or the characterisation of the deviating systembehaviour results in a known pattern of behavior (not depicted), thiscan be associated with a resolution strategy (not depicted). Such aresolution strategy is also based on empirical values, whereby theseempirical values can also be largely systematised.

With regard to systematized empirical values, it should be specificallyconsidered that, depending on the type and severity of the deviation ofthe monitored output quantity from the expected output quantity, acertain error can be inferred. Preferably this conclusion is valid or atleast transferable for a plurality of different system components (notdepicted) and a plurality of different cleaning systems (not depicted).

For example, an increased power consumption (not depicted) of a cleaningfluid pump (not depicted) and thus a deviation of the system behaviourmay lead to the conclusion that there is an error in the cleaning system(not depicted). It is especially conceivable here that the cleaningfluid pump (not depicted) will age, whereby it is particularlyconceivable in concrete terms that a higher energy requirement will haveto be used for a controlled pump pressure of the cleaning fluid pump(not depicted). Alternatively, it is especially conceivable that thereis a blockage (not depicted) in the flow channel (not depicted)downstream of the cleaning fluid pump (not depicted), which causes anincreased back pressure which influences the system behaviour of thecleaning fluid pump (not depicted). Depending on the situation, adifferentiation to localize the cause of the diagnosed deviation can bemade by comparing another value of the output quantity. For this,experience values are necessary, which can be available in a list inparticular.

This also shows that a deviation between an expected output quantity anda monitored output quantity of a system behaviour of a system component(not depicted) does not have to be caused by the monitored systemcomponent itself.

If there is a blockage in front of the cleaning fluid pump (notdepicted), then within the scope of a conceivable resolution strategyfor eliminating the deviation with on-board means, concreteconsideration should be given to specifically increasing the cleaningfluid pump (not depicted) pressure, as a result of which the blockagecan be released if necessary and flushed out of the cleaning system (notdepicted). In particular, a selection of a resolution strategy accordingto the seventh aspect of the invention is being considered.

When implementing a resolution strategy, particular consideration shouldbe given to implementing the resolution strategy according to the eighthaspect of the invention.

If a selected and implemented resolution strategy is successful, asystem behaviour of the system component will result which correspondsto the expected system behaviour.

It should be expressly pointed out that the diagnostic method describedhere can be applied to any system component (not depicted). If asufficient number of sensors (not depicted) or measuring devices (notdepicted), a sufficient number of experience values regarding theexpected system behaviour of one or more system components (notdepicted) and a list (not depicted) of potentially successful resolutionstrategies are available, a large number of occurring deviations can becorrected with on-board means (not depicted). Deviations of the systembehaviour which cannot be repaired with on-board means (not depicted)can also be detected at an early stage and repaired within the scope ofregular or early maintenance, whereby a possible extension of possibledamage in the other case can be prevented advantageously.

Various variants are possible for the “Perform diagnostic method”process step.

According to a first variant, the perform diagnostic method steprequires a list (not depicted) with at least one threshold value (notdepicted) for an output quantity. This threshold value is an individualvalue for each output quantity and can also depend on the input quantityand the system component considered.

If a monitored output quantity exceeds and/or falls below anindividually associated threshold value, there is a deviation that canbe characterized, particularly by a further output quantity ifnecessary. According to this first variant, whether exceeding or fallingbelow a respective threshold value leads to a deviation depends on theindividually evaluated output quantity. This can be defined togetherwith the threshold value and stored in the list.

Furthermore, it is conceivable that a resolution strategy is known fromempirical values with which the particular deviation can be eliminatedagain, especially after the seventh and/or eighth aspect of theinvention.

According to a second variant it is conceivable that an expected systembehaviour of a system component is described by a dependency table (notdepicted), especially by a dependency table (not depicted), which hasbeen created according to the first steps of a method according to thefifth aspect of the invention.

A dependency table (not depicted) describes discrete empirical valuesfor the system behaviour of one system component (not depicted) at atime, so that an empirical value must first be selected from thedependency table (not depicted) before comparison with the monitoredoutput quantity. In this regard, it should be specifically considered toselect the experience value from the dependency table (not depicted) inthe form of a data set (not depicted) which is best suited by comparingthe input quantity, in particular best defined by the shortest Euclideandistance with respect to the input quantity between a data set (notdepicted) stored in the dependency table (not depicted) and the observedvalue for the input quantity during the observation of the outputquantity in the context of the diagnostic method.

Alternatively, it should be considered to select the two best fittingand adjacent experience values (not depicted) in the form of two datasets (not depicted) from the dependency table (not depicted) and tointerpolate between these two experience values according to theobserved input quantity.

If a difference is found between the expected and observed outputquantity, a further characterisation may be carried out by means of anappropriate procedure, in particular a procedure according to the sixthaspect of the invention and the possible settlement of the deviation bymeans of a resolution strategy, in particular the procedures accordingto the seventh and/or eighth aspect of the invention.

According to a third variant, it is proposed that an expected systembehaviour of a system component (not depicted) is represented bysystematic dependence (not depicted), in particular by systematicdependence (not depicted) according to the fifth aspect of theinvention.

A systematic dependence (not depicted) can describe the system behaviourcontinuously as a function of the input quantity, so that a selection orinterpolation between empirical values as described above for the secondvariant is advantageously not necessary.

If a deviation between a monitored output quantity and an expectedoutput quantity is detected, it is suggested to proceed according to thesecond variant.

Just like the dependency table (not depicted) and the threshold value(not depicted), the systematic dependence (not depicted) is inparticular valid for one system component (not depicted), so that adeviating systematic dependence (not depicted) or a deviating dependencytable (not depicted) or a deviating threshold value (not depicted) couldnecessarily be selected for a consideration of a deviating systemcomponent (not depicted).

In the diagnostic procedure shown in FIG. 18 , a procedure according tothe first variant is described in which an individual threshold value(not depicted) is used to decide whether or not there is a deviation ofthe system behaviour for the diagnosed system component (not depicted).

If there is no deviation, the diagnostic method can be stopped oralternatively continued with the same or a different system component(not depicted).

If a deviation is detected, further characterisation of the deviationmay be made, in particular according to the sixth aspect of theinvention and selection of a resolution strategy, in particularselection according to the seventh aspect of the invention.

Subsequently, the diagnostic method may also be stopped or alternativelycontinued with the same or a different system component (not depicted).

Furthermore, an implementation of the resolution strategy (not depicted)is conceivable afterwards, in particular an implementation according tothe eighth aspect of the invention.

Optionally, a diagnostic method is proposed in FIG. 18 , whereby aself-diagnosis of the electronic control unit (not depicted) of thecleaning system (not depicted) is carried out after the start of thediagnostic method. In particular, the following measures could beconsidered: read for over current (not depicted) and/or memory check(not depicted) and/or communication check (not depicted) with theelectronic control unit (not depicted) of the motor vehicle (notdepicted) and/or temperature check (not depicted) and/or motion sensing(not depicted) and/or pressure sensing (not depicted) and/or overvoltageprotection check (not depicted) and/or short circuit check (notdepicted).

Furthermore, it is optionally proposed to check all system components(not depicted) connected to the electronic control unit (not depicted)of the cleaning system (not depicted). In particular, the followingmeasures should be considered: read for short circuit (not depicted)and/or open circuit (not depicted) and/or impedance matching (notdepicted) and/or current check (not depicted) and/or bus communicationcheck (not depicted).

The cleaning method (unmarked) in FIG. 19 consists of the proceduralsteps:

-   -   Check soiling status/availability of a sensor;    -   Determine cleaning strategy;    -   Optimize resource requirement; and    -   Perform defined cleaning process(es).

The cleaning method (unmarked) provided here can run autonomously and/orbe started manually.

As a first step, an actual availability check (unmarked) is proposed, inparticular an actual availability check for all sensors installed on amotor vehicle (not depicted). The actual availability gives a referenceto the soiling status of an associated sensor (not depicted), so thatthe actual availability can also be used to quantify the soiling statusof each associated sensor (not depicted).

The soiling status/availability of a sensor can preferably be checkedserially or in parallel for all sensors (not depicted).

The second step refers to the determination of a cleaning strategy(unmarked), especially a cleaning strategy (not depicted) depending on acleaning mode (not depicted), especially a cleaning strategy (notdepicted), which is determined by a method according to the fourthaspect of the invention.

The cleaning strategy (not depicted) preferably specifies when, whereand how to clean what, preferably with the objective of using as fewcleaning resources (not depicted) as possible to achieve a defined goal.The cleaning strategy (not depicted) refers to all surfaces (notdepicted) of a motor vehicle (not depicted) which are connected to atleast one sensor.

After defining a cleaning strategy, it is proposed to optimize aresource requirement (not depicted) for each cleaning process (notdepicted). A cleaning process (not depicted) is assigned to at least onesensor (not depicted) and set up to improve the soiling status oravailability of the corresponding sensor (not depicted).

The optimization of the resource requirement (not depicted) shouldcontribute to the definition of a cleaning process (not depicted), whichis expected to improve the availability of an associated sensor (notdepicted) as much as possible by using as few resources as possible. Theoptimization of the cleaning process (not depicted) refers to a surface(not depicted) that is in an active connection with at least one sensor(not depicted).

In particular, the optimization of the resource requirement (notdepicted) according to a method according to the third aspect of theinvention can be carried out.

Furthermore, the optimization of the resource requirement (not depicted)could preferably be carried out serially or in parallel for all surfaces(not depicted) that are in an active connection with at least one sensor(not depicted).

It should be expressly pointed out that the preceding procedural step ofdetermining a cleaning strategy (unmarked) may already implicitlyinclude the procedural step optimize resource requirement (unmarked),especially in the case where the cleaning strategy (not depicted) isdetermined according to the fourth aspect of the invention. However,this is not necessarily the case, so that the steps can also be carriedout separately and one after the other.

Once at least one cleaning process (not depicted) has been defined bythe above procedure, it is executed according to the next step(unmarked), although execution does not necessarily require it to beexecuted simultaneously. It is also conceivable that a defined cleaningprocess (not depicted) is only executed if a defined start condition(not depicted) for the cleaning process (not depicted) is fulfilled.

In particular, when implementing a cleaning process (not depicted), itis preferable to consider an implementation within the framework of acleaning method (not depicted) according to the first aspect of theinvention.

LIST OF REFERENCE NUMERALS

-   -   10 Cleaning method    -   11 Cleaning device    -   12 Course of time    -   14 Motor vehicle    -   16 Cleaning system    -   18 Electronic control unit    -   20 Surface    -   22 Surface    -   24 Surface    -   26 Surface    -   28 Surface    -   30 Cleaning process    -   30 d Resource requirement    -   32 Cleaning process    -   32 d Resource requirement    -   34 Cleaning process    -   34 d Resource requirement    -   36 Cleaning process    -   36 d Resource requirement    -   38 Cleaning process    -   38 a Cleaning period of cleaning process    -   38 b Start time of cleaning process    -   38 c End time of cleaning process    -   38 d Resource requirement    -   40 Cleaning process    -   40 a Cleaning period of cleaning process    -   40 b Start time of cleaning process    -   40 c End time of cleaning process    -   40 d Resource requirement    -   50 Sensor    -   52 Sensor    -   54 Sensor    -   56 Sensor    -   56 a Sensor    -   56 b Sensor    -   58 Sensor    -   60 Cleaning fluid distribution system    -   62 Cleaning fluid reservoir    -   63 Cleaning fluid reservoir level sensor    -   64 Cleaning fluid    -   66 Cleaning fluid pump    -   68 Air pressure reservoir    -   70 Nozzle    -   72 Nozzle    -   74 Nozzle    -   76 a Nozzle    -   76 b Nozzle    -   78 a Nozzle    -   78 b Nozzle    -   80 Cleaning fluid line    -   82 Cleaning fluid line    -   84 Cleaning fluid line    -   86 Cleaning fluid line    -   88 Cleaning fluid line    -   90 wiping element    -   92 wiping element    -   94 wiping element    -   100 Measured quantity    -   100 b Measured value of measured quantity at start time of        cleaning period    -   100 c Measured value of measured quantity at end time of        cleaning period    -   100D Difference between measured values of measured quantity at        end time and at start time of cleaning period    -   102 Measured quantity    -   102 b Measured value of measured quantity at start time of        cleaning period    -   102 c Measured value of measured quantity at end time of        cleaning period    -   102D Difference between measured values of measured quantity at        end time and at start time of cleaning period    -   104 Measured quantity    -   104 b Measured value of measured quantity at start time of        cleaning period    -   104 c Measured value of measured quantity at end time of        cleaning period    -   104D Difference between measured values of measured quantity at        end time and at start time of cleaning period    -   106 Measured quantity    -   106 b Measured value of measured quantity at start time of        cleaning period    -   106 c Measured value of measured quantity at end time of        cleaning period    -   106D Difference between measured values of measured quantity at        end time and at start time of cleaning period    -   107 Measured quantity    -   107 b Measured value of measured quantity at start time of        cleaning period    -   107 c Measured value of measured quantity at end time of        cleaning period    -   107D Difference between measured values of measured quantity at        end time and at start time of cleaning period    -   108 Measured quantity    -   108 b Measured value of measured quantity at start time of        cleaning period    -   108 c Measured value of measured quantity at end time of        cleaning period    -   108D Difference between measured values of measured quantity at        end time and at start time of cleaning period    -   110 Control quantity    -   110V Value of control quantity    -   111 Control quantity    -   111V Value of control quantity    -   112 Control quantity    -   112V Value of control quantity    -   113 Control quantity    -   113V Value of control quantity    -   114 Control quantity    -   114V Value of control quantity    -   115 Control quantity    -   115V Value of control quantity    -   116 Control quantity    -   116V Value of control quantity    -   117 Control quantity    -   117V Value of control quantity    -   118 Control quantity    -   118V Value of control quantity    -   119 Control quantity    -   119V Value of control quantity    -   120 Systematic dependence, preferably systematic dependence for        a system behaviour of a cleaning system    -   120D Systematic dependence between difference between measured        values of measured quantity at end time and at start time of        cleaning period and measured value of control quantity    -   120R Systematic dependence between resource requirement and        measured value of control quantity    -   122 Systematic dependence, preferably systematic dependence for        a system behaviour of a soiling process    -   124 Systematic dependence, preferably systematic dependence for        a system behaviour of a system component of a cleaning system    -   130 Control quantity sensor    -   132 Control quantity sensor    -   134 Control quantity sensor    -   140 Process quantity    -   141 Process quantity    -   142 Process quantity    -   143 System related process quantities    -   144 Environmental process quantities    -   145 Process quantity    -   146 Process quantity    -   147 Process quantity    -   150 Data processing system    -   152 Electronic data processing and evaluation system    -   154 Database    -   156 Control quantity acquisition and setting system    -   158 Process quantity acquisition system    -   160 Measured quantity acquisition system    -   170 Process quantity sensor    -   171 Process quantity sensor    -   172 Process quantity sensor    -   175 Process quantity sensor    -   176 Process quantity sensor    -   177 Process quantity sensor    -   180 Data link    -   181 Data link    -   182 Data link    -   183 Data link    -   184 Data link    -   185 Data link    -   186 Data link    -   187 Data link    -   188 Data link    -   189 Data link    -   190 Data link    -   191 Data link    -   192 Data link    -   193 Data link    -   194 Data link    -   195 Data link    -   196 Data link    -   197 Data link    -   198 Data link    -   200 System    -   202 Input quantity    -   204 Output quantity    -   210 Data representing measured quantity    -   212 Data representing measured quantity    -   214 Data representing measured quantity    -   220 Availability    -   221 Actual availability    -   222 Availability    -   223 Expected availability    -   224 Availability    -   225 Availability at which system/sensor can no longer fulfill        its requirements    -   226 Availability at which system/sensor can fully fulfill its        requirements    -   227 Threshold of availability    -   228 Threshold of availability    -   229 Expected gain in availability    -   230 Cleaning fluid valve    -   232 Cleaning fluid valve    -   234 Cleaning fluid valve    -   236 Cleaning fluid valve    -   238 Cleaning fluid valve    -   240 Cleaning fluid multi way valve    -   242 Cleaning fluid multi way valve    -   250 Cleaning mode    -   260 First availability    -   262 Second availability    -   264 Change of availability/loss of availability    -   270 Distance    -   272 Distance yet to be covered    -   274 Expected distance    -   280 Operating time    -   282 Operating time yet to be covered    -   284 Expected operating time    -   AD Access dependency table and/or systematic dependence    -   BDT Build dependency table    -   BDTS1 Build dependency table step one    -   BDTS2 Build dependency table step two    -   BDTS3 Build dependency table step three    -   BDTS4 Build dependency table step four    -   DCQS Derive control quantity setpoint    -   DCQSS1 Derive control quantity setpoint step one    -   DCQSS2 Derive control quantity setpoint step two    -   DP1 Data set    -   DP2 Data set    -   DP3 Data set    -   DP4 Data set    -   DSD Derive systematic dependence    -   DSDS1 Derive systematic dependence step one    -   DSDS2 Derive systematic dependence step two    -   DSDS3 Derive systematic dependence step three    -   DT Dependency table    -   MCS Method for selecting a surface to be cleaned    -   MCSS1 Method for selecting a surface to be cleaned step one    -   MCSS2 Method for selecting a surface to be cleaned step two    -   MCSS3 Method for selecting a surface to be cleaned step three    -   MCSS4 Method for selecting a surface to be cleaned step four    -   MCSS5 Method for selecting a surface to be cleaned step five    -   MDSD1 Method for indirectly deriving a systematic dependence    -   MDSD2 Method for indirectly deriving a systematic dependence    -   MDSD3 Method for indirectly deriving a systematic dependence    -   MORR Method for optimizing a resource requirement    -   SCQS Store control quantity setpoint    -   UEA Method to determine an expected availability at a distance        or operating time of the motor vehicle yet to be covered    -   UEAa Step a of the method to determine an expected availability        at a distance or operating time of the motor vehicle yet to be        covered    -   UEAb Step b of the method to determine an expected availability        at a distance or operating time of the motor vehicle yet to be        covered    -   UEAT Method to determine an expected distance or operating time        of the motor vehicle yet to be covered when reaching a threshold        of availability    -   UEATa Step a of the method to determine an expected distance or        operating time of the motor vehicle yet to be covered when        reaching a threshold of availability    -   UEATb Step b of the method to determine an expected distance or        operating time of the motor vehicle yet to be covered when        reaching a threshold of availability    -   UEGAT Method to determine an expected gain in availability,        whereby the sum of the current availability and the expected        gain in availability is sufficient to achieve a distance or        operating time to be covered by the motor vehicle in such a way        that a threshold of availability is not exceeded    -   UEGATa Step a of the method to determine an expected gain in        availability, whereby the sum of the current availability and        the expected gain in availability is sufficient to achieve a        distance or operating time to be covered by the motor vehicle in        such a way that a threshold of availability is not exceeded

1. A method for optimizing a resource requirement for a cleaning processof a surface of a motor vehicle, whereby a sensor is operativelyconnected to the surface, whereby the method uses data from a dependencytable for a system behavior of a cleaning system of the motor vehicle,whereby the dependency table includes data sets that each have an inputquantity of the cleaning system and an output quantity of the cleaningsystem, whereby the output quantity depends on the input quantity of thesystem behavior of the cleaning system, whereby the dependency tableincludes data sets for the system behavior of the cleaning systembetween at least one control quantity of the cleaning process, anavailability of the sensor at a start time of the cleaning process andan availability of the sensor at an end time of the cleaning process,wherein the resource requirement of the cleaning process depends on theat least one control quantity, the method comprising steps of: accessingthe data of the dependency table from at least one of a database, anelectronic data processing and evaluation unit, or an electronic controlunit; deriving a difference between the availability of the sensor at anend time of the cleaning process and the availability of the sensor at astart time of the cleaning process for each data set of the dependencytable; deriving a ratio of the difference to the respective resourcerequirement for each data set of the dependency table; and selecting acontrol quantity of the data set that includes a highest value of theratio.
 2. (canceled)
 3. The method for optimizing the resourcerequirement for the cleaning process of a surface of a motor vehicleaccording to claim 1, wherein the dependency table includes a dependencyto a process quantity including at least one of a humidity, atemperature in a vicinity of the motor vehicle, a rainfall, a snowfallquantity, or a coordinate of the motor vehicle; and wherein, prior tothe selection of the control quantity, the data sets taken into accountin the selection of the control quantity from the dependency table arefirst restricted to an area which deviates from the respective processquantity including at least one of: a current humidity, forecasthumidity along a planned itinerary, a current temperature in thevicinity of the motor vehicle, a forecast temperature along the planneditinerary, a current rainfall, a forecast rainfall along the planneditinerary, a current snowfall quantity, a forecast snowfall quantityalong the planned itinerary, a coordinate of the motor vehicle, or aforecast coordinate of the motor vehicle along the planned itinerary, byless than 20%.
 4. The method for optimizing the resource requirementaccording to claim 1, wherein the dependency table includes a dependencyto the availability of the sensor at the start time of the cleaningprocess; and wherein prior to the selection of the control quantity, thedata sets taken into account in the selection of the control quantityfrom the dependency table are first restricted to an area which deviatesfrom an actual availability of the sensor or an expected availability ofthe sensor at a point on a planned route by less than 20%, 10%, or 5%,by determining the expected availability at a distance or an operatingtime of the motor vehicle yet to be covered.
 5. The method foroptimizing the resource requirement according to claim 1, wherein thedependency table includes a dependency to the availability of the sensorat the start time of the cleaning process; wherein prior to theselection of the control quantity, the data sets taken into account inthe selection of the control quantity from the dependency table arefirst restricted to an area where the availability of the sensor at thestart time of the cleaning process is less than or equal to an actualavailability of the sensor; and wherein the availability of the sensorat the start time of the cleaning process associated with the controlquantity is saved with the control quantity as a control quantitysetpoint.
 6. The method for optimizing the resource requirementaccording to claim 1, wherein prior to the selection of the controlquantity, the data sets taken into account in the selection of thecontrol quantity from the dependency table are first limited to an areathat an expected gain in availability is not more than 20% above theavailability with which a current itinerary of the motor vehicle iscarried out without at least one of unintentional impairment of sensorfunctionality or until a threshold of availability of not more than 10%,by determining an expected gain in availability, whereby a sum of acurrent availability and the expected gain in availability achieves adistance or an operating time to be covered by the motor vehicle suchthat a threshold of availability is not exceeded.
 7. The method foroptimizing the resource requirement according to claim 1, wherein priorto the selection of the control quantity, the data sets taken intoaccount in the selection of the control quantity from the dependencytable are first limited to an area that an expected gain in availabilityachieves a distance or an operating time to a subsequent cleaningprocess without falling below a threshold of availability and not morethan 20% above the gain in availability to achieve a distance or anoperating time to the subsequent cleaning process without falling belowa threshold of availability, not more than 10% or 5%, by determining anexpected distance or an expected operating time of the motor vehicle yetto be covered when reaching a threshold of availability, by determiningan expected gain in availability, whereby a sum of a currentavailability and the expected gain in availability achieves a distanceor an operating time to be covered by the motor vehicle such that athreshold of availability is not exceeded.
 8. The method for optimizingthe resource requirement according to claim 1, further comprisingselecting a first control quantity and selecting a second controlquantity, wherein a first control quantity setpoint defines a firstcleaning process and a second control quantity setpoint defines a secondcleaning process for a sequence of cleaning processes, the secondcleaning process being performed after completion of the first cleaningprocess.
 9. The method for optimizing the resource requirement accordingto claim 1, wherein the method is performed in series or in parallel forat least two, three, four, or five or more surfaces to be cleaned. 10.The method for optimizing the resource requirement according to claim 1,wherein the control quantity is selected using a multi-criteriaoptimization procedure.
 11. A method according to claim 1 implemented ina cleaning method for a resource efficient cleaning that is aresource-saving cleaning, of at least one surface of the motor vehicle,wherein the motor vehicle exhibits a cleaning system and at least onesensor, wherein the sensor is operatively connected to one surface,wherein the cleaning method exhibits at least one cleaning process,wherein the cleaning process is adapted to clean one surface andexhibits a cleaning period comprising a start time and an end time,wherein the cleaning system exhibits an electronic control unit, acleaning fluid distribution system, preferably comprising at least onefluid reservoir, at least one nozzle, and at least one cleaning fluidline, wherein the sensor is adapted to: detect at least one of: ameasured quantity of an availability of the sensor, a process quantityof at least one of: a humidity and/or a temperature in a vicinity of themotor vehicle, a rainfall and/or a snowfall quantity, or a coordinate ofthe motor vehicle, a control quantity, transmit the measured quantity tothe electronic control unit, wherein the nozzle is adapted to bring acleaning fluid into operative connection with the surface, wherein theelectronic control unit is adapted to control and/or regulate thecleaning process by means of at least one control quantity of thecleaning process, wherein the resource requirement of the cleaningprocess depends on a control quantity setpoint, wherein the electroniccontrol unit controls and/or regulates the resource efficient cleaningapplying the control quantity setpoint.
 12. The method according toclaim 11, wherein the electronic control unit controls and/or regulatesthe resource efficient cleaning depending on an actual measured quantityvalue of an actual availability of the sensor.
 13. The method accordingto claim 1, further comprising using the control quantity setpoint foroptimizing the resource requirement.
 14. The method according to claim11, the method being used in a cleaning system including an electroniccontrol unit, and a cleaning fluid distribution system, wherein thecleaning fluid distribution system comprises at least one fluidreservoir, at least one nozzle, and at least one cleaning fluid line,wherein the cleaning system is adapted to optimize the resourcerequirement.
 15. The method according to claim 14, wherein at least oneof: the motor vehicle includes a cleaning system, or the motor vehicleis adapted to perform at least one of: execute a cleaning method for theresource efficient cleaning, optimize the resource requirement, or usethe control quantity setpoint to optimize the resource requirement. 16.A method for optimizing a resource requirement for a cleaning process ofa surface of a motor vehicle, wherein a sensor is operatively connectedto the surface, whereby the method uses a systematic dependence for asystem behavior of a cleaning system of the motor vehicle, whereby thesystematic dependence includes data sets that each have an inputquantity of the cleaning system and an output quantity of the cleaningsystem, whereby the output quantity depends on the input quantity of thesystem behavior of the cleaning system, whereby the systematicdependence includes data sets for the system behavior of the cleaningsystem between at least one control quantity of the cleaning process, anavailability of the sensor at a start time of the cleaning process, andan availability of the sensor at an end time of the cleaning process,wherein the resource requirement of the cleaning process depends on thecontrol quantity, the method comprising steps of: accessing thesystematic dependence from at least one of a database, an electronicdata processing and evaluation unit, or an electronic control unit;deriving a course of a difference between the availability of the sensorat an end time of the cleaning process and the availability of thesensor at a start time of the cleaning process for a course of thesystematic dependence; deriving a course of a ratio of the course of thedifference to a course of the respective resource requirement for thecourse of the systematic dependence; selecting the control quantitywhich belongs to a point in the course of the ratio exhibiting a highestvalue of the ratio; and storing the control quantity of the data set asa control quantity setpoint in the at least one of the database, theelectronic data processing and evaluation unit, or the electroniccontrol unit.
 17. The method for optimizing the resource requirement forthe cleaning process according to claim 16, wherein the systematicdependence includes a dependency to a process quantity including atleast one of a humidity, a temperature in a vicinity of the motorvehicle, a rainfall, a snowfall quantity, or a coordinate of the motorvehicle; and wherein, prior to the selection of the control quantity, anarea of the systematic dependence taken into account in the selection ofthe control quantity is first restricted to an area which deviates fromthe respective process quantity including at least one of a currenthumidity, a forecast humidity along a planned itinerary, a currenttemperature in the vicinity of the motor vehicle, a forecast temperaturealong the planned itinerary, a current rainfall, a forecast rainfallalong the planned itinerary, a current snowfall quantity, a forecastsnowfall quantity along the planned itinerary, a coordinate of the motorvehicle, or a forecast coordinate of the motor vehicle along the planneditinerary, by less than 20%.
 18. The method for optimizing the resourcerequirement according to claim 16, wherein the systematic dependenceincludes a dependency to the availability of the sensor at the starttime of the cleaning process; and wherein prior to the selection of thecontrol quantity, an area of the systematic dependence taken intoaccount in the selection of the control quantity is first restricted toan area which deviates from an actual availability of the sensor or anexpected availability of the sensor at a point on a planned route byless than 20%, by determining the expected availability at a distance oran operating time of the motor vehicle yet to be covered.
 19. The methodfor optimizing the resource requirement according to claim 16, whereinthe systematic dependence includes a dependency to the availability ofthe sensor at the start time of the cleaning process; wherein prior tothe selection of the control quantity an area of the systematicdependence taken into account in the selection of the control quantityis first restricted to an area where the availability of the sensor atthe start time of the cleaning process is less than or equal to anactual availability of the sensor; and wherein the availability of thesensor at the start time of the cleaning process associated with thecontrol quantity is saved with the control quantity as a controlquantity setpoint.
 20. The method for optimizing the resourcerequirement according to claim 16, wherein prior to the selection of thecontrol quantity an area of the systematic dependence taken into accountin the selection of the control quantity is first limited to an areathat an expected gain in availability is not more than 20% above theavailability with which a current itinerary of the motor vehicle iscarried out without unintentional impairment of sensor functionality oruntil a threshold of availability is reached, preferably not more than10%, by determining an expected gain in availability, whereby a sum of acurrent availability and the expected gain in availability achieves adistance or an operating time to be covered by the motor vehicle suchthat a threshold of availability is not exceeded.
 21. The method foroptimizing the resource requirement according to claim 16, wherein priorto the selection of the control quantity, an area of the systematicdependence taken into account in the selection of the control quantityare first limited to an area that an expected gain in availabilityachieves a distance or an operating time to a subsequent cleaningprocess without falling below a threshold of availability and not morethan 20% above the gain in availability necessary to achieve thedistance or the operating time to the subsequent cleaning processwithout falling below a threshold of availability not more than 10%, bydetermining an expected distance or an expected operating time of themotor vehicle yet to be covered when reaching a threshold ofavailability, by determining an expected gain in availability, whereby asum of a current availability and the expected gain in availabilityachieves a distance or an operating time to be covered by the motorvehicle in such a way that a threshold of availability is not exceeded.